Title: Data Dissemination and Fusion
1Data Dissemination and Fusion in Sensor Networks
2The Need for Data Dissemination and Fusion
- Energy efficiency is an essential factor
therefore, short-range hop-by-hop communication
is preferred over direct long-range communication
to the destination - Since sensor network contains large amount of
data for the end user, methods of combining or
aggregating data into small set of information is
necessary and contributes to energy savings - Data aggregation (aka data fusion) can combine
unreliable data readings to produce accurate
signal by improving the common signal and
reducing the noise
3Taxonomy of Data Delivery Models in Wireless
Sensor Networks
- Wireless sensor networks are classified according
to their data delivery model into the following
categories Kulik 2002 - Continuous
- LEACH Heinzelman 2000, 2002 is designed for
routing data to base stations in static wireless
sensor networks - TEEN (Threshold sensitive Energy Efficient sensor
Network Protocol) Agrawal 2001 and PEGASIS
(Power Efficient GAthering in Sensor Information
Systems) Lindsey 2001 are both proposed as
improvements to LEACH - Observer-initiated
- In Directed Diffusion Intanagonwiwat 2000,
data are named using attribute-value pairs and
sensed information in the network can be
associated with such a pair. The sensor nodes
send queries expressing their interest for sensed
information satisfying a specific criteria
4Taxonomy of Data Delivery Models in Wireless
Sensor Networks
- Event-driven
- SPIN (Sensor network Protocols via Information
Negotiation) Kulik 2002 are set of protocols
designed to disseminate data to all nodes in the
network - Hybrid
- The above three approaches can coexist in the
same network
5Directed DiffusionIntanagonwiwat 2000
- Motivated by scaling, robustness and energy
efficiency requirements - Directed diffusion is data-centric in that all
communication is for named data - Data generated by sensor nodes is named using
attribute-value pairs - All nodes in the network are application-aware
- A node requests data by sending interests for
named data - A sensing task is disseminated via sequence of
local interactions throughout the sensor network
as an interest for named data - Nodes diffusing the interest sets up their own
caches and gradients within the network to which
channel the delivery of data - During the data transmission, reinforcement and
negative reinforcement are used to converge to
efficient distribution - Intermediate nodes fuse interests, aggregate,
correlate or cache data
6Directed DiffusionIntanagonwiwat 2000
- Assumes that sensor networks are task-specific
the task types are known at the time the sensor
network is deployed - An essential feature of directed diffusion is
that interest, data propagation and data
aggregation are determined by local interactions - Focused on design of dissemination protocols for
tasks and events - Naming
- Task descriptions are named (specifies an
interest for data matching the list of
attribute-value pairs) and also called as
interest - Example task Every I ms, for the next T
seconds, send me a location of any four-legged
animal in subregion R of the sensor field. - task four-legged animal // detect animal
location - interval 20 ms // send back events every 20 ms
- duration 10 seconds // for the next 10
seconds - rect -100, 100, 200, 400 // from sensors
within rectangle
7Directed DiffusionIntanagonwiwat 2000
- Naming
- A sensor detecting an animal may generate the
following data - task four-legged animal // type of animal seen
- instance horse // instance of this type
- location 150, 200 // node location
- intensity 0.5 // signal amplitude measure
- confidence 0.85 // confidence in the match
- timestamp 013045 // event generation time
- Interests and Gradients
- Interest is generally given by the sink node
- For each active task, sink periodically
broadcasts an interest message to each of its
neighbors (including rect and duration
attributes) - Sink periodically refreshes each interest by
re-sending the same interest with monotonically
increasing timestamp attribute for reliability
purposes
8Directed DiffusionIntanagonwiwat 2000
- Interests and Gradients
- Every node maintains an interest cache where each
item in the cache corresponds to a distinct
interest (different type, interval attributes
with disjoint rect attributes) - Interest entries in the cache do not contain
information about the sink - In some cases, definition of distinct interests
allows interest aggregation - The interest entry contains several gradient
fields, up to one per neighbor - When a node receives an interest, it determines
if the interest exists in the cache - If no matching exist, the node creates an
interest entry - This entry has single gradient towards the
neighbor from which the interest was received
with specified data rate - Individual neighbors can be distinguished by
locally unique identifiers - If the interest entry exists, but no gradient for
the sender of interest - Node adds a gradient with the specified value
- Updates the entrys timestamp and duration fields
9Directed DiffusionIntanagonwiwat 2000
- Interests and Gradients
- If there exists both entry and a gradient,
- The node updates the entrys timestamp and
duration fields - When a gradient expires, it is removed from its
interest entry - When all gradients for an interest entry have
expired, the interest entry is removed from the
cache - After receiving an interest, a node may re-send
the interest to subset of its neighbors - To the neighbors, it may seem that interest
originated from the sending node even though it
may have been generated a distant sink. This
represents a local interaction - This way, interest diffuse throughout the network
and not each interest have been sent to all the
neighbors if a node sent matching interest
recently - Gradient specifies data rate (value) and a
direction in directed diffusion, whereas the
values can be used to probabilistically forward
data in different paths in other sensor networks
10Directed DiffusionIntanagonwiwat 2000
- Data propagation
- Data message is unicast individually to the
relevant neighbors - A node receiving a data message from its
neighbors checks to see if matching interest
entry in its cache exists according the matching
rules described - If no match exist, the data message is dropped
- If match exists, the node checks its data cache
associated with the matching interest entry - If a received data message has a matching data
cache entry, the data message is dropped - Otherwise, the received message is added to the
data cache and the data message is re-sent to the
neighbors - Data cache keeps track of the recently seen data
items, preventing loops - By checking the data cache, a node can determine
the data rate of the received events
11Directed DiffusionIntanagonwiwat 2000
- Reinforcement
- After the sink starts receiving low data rate
events, it reinforces one neighbor in order to
draw down higher quality (higher data rate)
events - This is achieved by data driven local rules
- To enforce a neighbor, the sink may re-send the
original interest with higher data rate - When the data rate is higher than before, the
node node must also reinforce at least one
neighbor - Reinforcement can be carried out from neighbors
to other neighbors in a particular path (i.e.,
when a path delivers an event faster than others,
sink attempts to use this path to draw down high
quality data) - In summary, reinforce one path, or part of it,
based on observed losses, delay variances, and so
on - Negative reinforce certain paths because resource
levels are low
12Directed DiffusionIntanagonwiwat 2000
Figure adapted from Intanagonwiwat 2000
13Directed DiffusionIntanagonwiwat 2000
- Advantages
- Data-centric dissemination
- Robust multi-path delivery
- Reinforcement-based adaptation to the empirically
best network path - Energy savings with in-network data aggregation
and caching - Gives designers the freedom to attach different
semantics to gradient values - Reinforcement can be triggered not only by
sources but also by intermediate nodes
14Directed DiffusionIntanagonwiwat 2000
- Disadvantages
- It may consume memory since all the attribute
list is being sent
- Suggestions/Improvements/Future Work
- Exploration of possible naming schemes
15Negotiation-Based Protocols for Disseminating
Information in Wireless Sensor Networks (SPIN
Protocols) Kulik 2002
- SPIN (Sensor Protocols for Information via
Negotiation) is a family of negotiation-based
information dissemination protocols which is
designed to address the deficiencies of classic
flooding by negotiation and resource-adaptation - SPIN disseminates each sensor readings to all
sensors in the network, treating all sensors as
potential sink nodes - Nodes using SPIN protocols names their data using
high-level data descriptors, called meta-data and
usage of meta-data negotiations eliminate
transmission of redundant data in the network - Communication decisions can be based upon both
application-specific knowledge of the data and
knowledge of the resources available to nodes
16SPIN Kulik 2002
- SPIN has two basic ideas
- Operate efficiently and conserve energy
communicate with each other about the sensor data
received already and the data needed still - Monitor and adapt changes in their own energy
resources extend the lifetime of the system - Four difference SPIN protocols
- SPIN-PP
- SPIN-EC
- SPIN-BC
- SPIN-RL
- Meta Data
- Used to uniquely and completely describe the data
being collected by sensors - If two pieces of actual data are distinguishable,
then their meta-data should also be
distinguishable - Since the format of meta-data is
application-specific, each application needs to
interpret and synthesize its own meta-data
17SPIN Kulik 2002
- Meta Data
- SPIN applications must define a meta-data format
for representing data that concerns with the
costs of storing, retrieving and managing the
meta-data - SPIN nodes uses three types of communication
messages - ADV (new data advertisement)
- REQ (request for data)
- DATA (data message)
- ADV and REQ messages contain only meta-data that
is smaller than the DATA message - SPIN Resource Management
- SPIN applications are resource-aware and
resource-adaptive - By knowing the resources at hand, the nodes makes
informed decisions about using their resources
effectively - SPIN specifies an interface that applications can
use to find out their available resources rather
than specifying a specific energy management
protocols
18SPIN Kulik 2002
- The Problem
- In conventional classic flooding, the source
nodes sends data to all its neighbors and the
neighbors check their record of already sent data
to see if they have forwarded the data to their
neighbors. If not, they forward the data and
update the record - This requires small amount of protocol state at
any node, disseminates data quickly in the
network where neither the bandwidth is scarce and
the links are error prone - The problems include implosion, overlap and
resource blindness - Implosion A node always sends data to its
neighbors without being concerned about - if the same data has been received by the
neighbors from other nodes - Overlap The nodes waste energy and bandwidth by
sending the overlapping data - Resource Blindness Nodes do not make decisions
based on the energy available
19SPIN Kulik 2002
- The Solution
- SPIN provides solution to the problems of
implosion and overlap by negotiating with each
other before transmitting data eliminates the
transmission of redundant data - Nodes poll their resources before transmitting or
processing data by probing the resource manager
which keeps track of the resource consumption - Nodes can make efficient decisions based on the
available energy level - The use of meta-data descriptors eliminates the
possibility of overlap since the nodes can name
the part of the data the nodes are interested in
receiving - Resource-awareness of local resources allow
sensors to make meaningful decisions to extend
longevity
20SPIN Kulik 2002
- SPIN Protocols
- 1. SPIN-PP A Threestage handshake protocol for
point-to-point media - This protocol works in three stages
(ADV-REQ-DATA) with each stage corresponding to
one of the messages - The node sends ADV message to its neighbors
- Neighbors check to see if they already have
received or requested this data - If not, the neighbors respond by sending REQ
message to the sender - The sender responds to the REQ message sent by
sending the actual DATA to the neighbors
requesting the data - If the neighbor already has the advertised data,
it does not send any message - Simplicity is the main strength, meaning that
nodes make simple decisions, resulting in usage
of small energy in computation - Each node only needs to know about its one hop
neighbors
21SPIN Kulik 2002
- SPIN Protocols
- 2. SPIN-EC SPIN-PP with low-energy threshold
- Adds simple energy-conservation heuristic to the
SPIN-PP protocol - When energy is abundant, SPIN-EC acts as SPIN-PP
protocol - Whenever energy comes close to low-energy
threshold, it adapts by reducing its
participation - The node will only participate in the full
protocol if it believes that it has enough energy
to complete the protocol without reaching below
the threshold value - It does not prevent nodes from receiving messages
such as ADV or REQ below its low-energy
threshold, but prevents the nodes to handle a
DATA message below the threshold
22SPIN Kulik 2002
- SPIN Protocols
- 3. SPIN-BC A Threestage handshake protocol for
broadcast media - Improves upon SPIN-PP for broadcast networks by
using cheap, one-to-many communications, meaning
that all messages are sent to broadcast address
and processed by all the nodes that are within
transmission range of the sender - This approach is often called broadcast-message-su
ppression - SPIN-BC has three main differences from SPIN-PP
are - All SPIN-BC nodes send their messages to the
broadcast address such that all nodes within the
transmission range of sender will receive message - Upon receiving ADV message, each node checks to
see if they already have the data. If not, node
sets a random timer to expire, uniformly chosen
from a predetermined interval. After timer
expires, the node sends an REQ message to the
broadcast address, including the original
advertiser in the header of message. When the
nodes who are not original advertiser receive the
REQ, they cancel their own request timers,
preventing from sending out redundant copies of
the same REQ - The nodes will send out the requested data to the
broadcast address only once to get the data all
its neighbors. It will not respond to multiple
requests of the same data
23SPIN Kulik 2002
- SPIN Protocols
- 4. SPIN-RL SPIN-BC for lossy networks
- Reliable version of SPIN-BC which disseminates
data through a broadcast network even in the
cases of network loses packets or communication
is asymmetric - Adds two adjustments to SPIN-BC to achieve
reliability - Each node maintains a record of which
advertisements it hears from which nodes, and if
does not receive the data within a set time after
request, node rerequests the data - Nodes limit the frequency with which they will
resend the data, meaning that it will wait for a
set time before responding to any additional
requests for the same data
24SPIN Kulik 2002
- Advantages
- Meta-data negotiation and resource adaptation
- Maintains only local information about the
nearest neighbors - Suitable for mobile sensors since the nodes base
their forwarding decisions on local neighborhood
information
- Disadvantages
- It cannot isolate the nodes that do not want to
receive information unnecessary power may be
consumed
25SPIN Kulik 2002
- Suggestions/Improvements/Future Work
- Study SPIN protocols in mobile wireless network
models - Develop more sophisticated resource-adaptation
protocols to use available energy well - Design protocols that make adaptive decisions
based not only on the cost of communicating data,
but also the cost of synthesizing it
26DIFS A Distributed Index for Features in Sensor
Networks Greenstein 2003
- This work considers searches over semantically
rich high-level events, and presents the design,
analysis, and numerical simulations of a
spatially distributed index that provides for
efficient index construction and range searches - The conventional approach to storing time series
data is to have all sensing node sending their
data to a central repository external to the
environment - While obtaining the flexibility of processing the
data, sending every sensor reading to external
site incurs high energy consumption - In addition, the links near a gateway or an
external storage repository can become
communication bottlenecks as the network size and
the sensed data increase - As a result, it may be advisable to store data
locally at or near the location of the generation
of the sensed data
27DIFS A Distributed Index for Features in Sensor
Networks Greenstein 2003
- One approach to retrieve this stored data is to
flood a query to all nodes that may have suitable
data and have those nodes send their response to
the querying node - In this approach, data is sent when and where it
is required - If some queries are originated within the sensor
network, it is not advisable to send the data to
an external site instead of sending it to the
internal querying data - If more data is collected than required, this
local storage approach increase energy savings - There are two extensions to this approach for
further energy savings - Data can be processed, aggregated, and/or pruned
while propagating towards the query sink
28DIFS A Distributed Index for Features in Sensor
Networks Greenstein 2003
- There are two extensions to this approach for
further energy savings - The developers of Directed Diffusion
Intanagonwiwat 2000,TAG Madden 2002, and
others describe specific forms of in-network
aggregation and pruning of data that can select
relevant data and produce statistics. This
approach uses data-centric routing that queries
are not directed towards individual nodes, but
they are stated only in terms of desired data - The data can be processed locally to identify
high-level events that of interest. These
events can refer directly to sensor readings. The
queries are directly for such events, and the
responses comprised of summarized data about
those events. Here, the routing is also
data-centric, but queries and responses interact
with higher-level abstractions
29DIFS A Distributed Index for Features in Sensor
Networks Greenstein 2003
- These energy savings approaches reduce the energy
required to respond to queries, but do not deal
with the cost of basic flood-then-respond
approach in that cost of flooding each query to
all possible nodes - Data-centric storage (DCS) approach Shenker
2002 avoids the flooding of queries -- all
events are named and stored at a network location
based on the name and queries for an event are
routed to appropriate network node where the
relevant data can be accessed - Storing data by name allows creation of a
mechanism between data and queries such that
queries need not be flooded - GHT Ratnasamy 2002 proposes a specific
solution to achieve DCS in which event names are
hashed to geographic locations and stored at the
node closest to the hashed location
30DIFS A Distributed Index for Features in Sensor
Networks Greenstein 2003
- DIFS extend the the data-centric storage
architecture to support range queries where only
events with attributes in a certain range are
desired. It provides for low average search and
storage communication requirements and tries to
balance these requirements over participating
nodes - DIMENSIONS Ganesan 2002 also relies on the
placement of data within the sensornet and use of
data-centric rendezvous points with lower level
sensor readings and produces a multiresolution
index (or view) of data - High-Level Events
- High-level events, such as a hot region or a
target detection, a map, or a histogram can be
described in many ways - The paper propose adding new data structures to
store high-level data abstractions to the simple
attribute types introduced by Diffusion - Such abstractions would be defined system-wide at
deployment time
31DIFS A Distributed Index for Features in Sensor
Networks Greenstein 2003
- Classification of Event Properties and
Relationships - Classification proposed has been designed with
the consideration of attribute range and
distribution queries - The goals of a system directed at binary events
such as zebra sightings are different from the
goals of providing range searches over events
that are each comprised of attributes with values - The goal of a search over binary events is to
determine the locations of those events and when
such events are rare, it is much more
energy-efficient to construct a rendezvous point
where events could register and queries could
search than to flood a search - Events defined by attributes with values that
fall within a specified range are less common,
i.e., there may be many hot regions in a network,
but few with a heat gradient with a slope greater
than s
32DIFS A Distributed Index for Features in Sensor
Networks Greenstein 2003
- Classification of Event Properties and
Relationships - For this reason, this paper develops a new method
to support range queries more efficiently and
proposes mechanisms to run on top of GHT to
address range queries - The high-level events are classified as follows
- Sensor value(s)
- Includes raw sensor values that comprise
high-level events, composite measurements and
summary statistics such as average, median, etc - Examples include the peak temperature of a hot
region, the speed that an animal target is moving - Sensor values can be search over a designed area
and they are represented as integers or floating
point numbers
33DIFS A Distributed Index for Features in Sensor
Networks Greenstein 2003
- Classification of Event Properties and
Relationships - Timing parameters
- Essential to know not only a specific value for a
region, but also how this value varies over time,
I.e., a hot region that has been hot for some
period of time - Spatial dimensions
- Refers to physical shape and location of an
event, i.e., hot regions larger than a given area - Regions can described as enclosing circles,
ellipses, or polygons and their points of
interest can be represented as integer or
floating point coordinates
34DIFS A Distributed Index for Features in Sensor
Networks Greenstein 2003
- Classification of Event Properties and
Relationships - Event Interrelationships
- In the spatial domain, relationships between
events translates to proximity or intersection,
i.e., is an area of high CO2 concentration also
an area of bright sunlight? - In the temporal domain, event interrelationships
translate to succession and temporal separation,
i.e., did an area of high CO2 concentration
happens immediately after bright sunlight?
Table 1 Event Property and Relationship
Classification
35DIFS A Distributed Index for Features in Sensor
Networks Greenstein 2003
- Storage and Search Architecture
- Time series data generated by sensor nodes is
locally processed by statistical and pattern
recognition engines to generate high-level events
that these events are stored locally where they
are created, and information about their various
attributes is inserted into indices - An interested user or an automaton poses queries
to these indices - The query results are found in the indices
themselves, at the storage nodes, and even at the
nodes that generate time series data - In terms of event generation and search, nodes
serve two functions - all nodes may be used to store raw time series
data and events - a subset of nodes serve as index nodes to
facilitate search
36DIFS A Distributed Index for Features in Sensor
Networks Greenstein 2003
Storage and Search Architecture
Figure 2 A storage and search architecture
37DIFS A Distributed Index for Features in Sensor
Networks Greenstein 2003
- Advantages
- DIFS efficiently supports range queries and
queries related to distribution of values in
space by using histograms, that direct queries to
the relevant nodes - The paper builds on an already proven technique
and simulation results show that DIFS
outperforming GHT in query and communication
costs - DIFS was designed to incorporate balancing of
communication load over the network by having
more than one query entry point and provision to
originate search at any node in the tree - DIFS is scalable to large number of searches or
stores as it eliminates the restriction of
propagating every data information to the root
and originating every query at the root
38DIFS A Distributed Index for Features in Sensor
Networks Greenstein 2003
- Disadvantages
- No mentioning about the failure of sensor nodes
at level of the hierarchy in the quad tree
structure of DIFS - In case of dense deployment, a uniform
distribution of data values causes the DIFS
algorithm exploring all the leaves hence not a
very good option as far as energy consumption is
considered - No mentioning about making the querying and event
insertion resilient to packet loss - Overhead incurred while maintaining extra parent
information
39DIFS A Distributed Index for Features in Sensor
Networks Greenstein 2003
- Suggestions/Improvements/Future Work
- Introduce dynamic repartitioning when the
distribution changes over a time period - To handle large queries, may be they can be split
into smaller sub-queries, encoding them to be
identified later and process them separately,
either locally or forwarding to other nodes that
have lesser traffic this will avoid energy
depletion of the really busy query access nodes - Handle data corruption at index nodes
- Improve DIFS search cost
- route the query using hierarchical dissemination,
as in structured replication, rather than sending
unicast messages to each of the covering nodes - route to nodes in the highest tree level that
will cover the entire query range, rather than
decomposing the query range into minimal covering
set
40Power-Efficient Data Dissemination in Wireless
Sensor Networks Cetintemel 2003
- Introduction
- This work presents a new event-based
communication model - The proposed protocol called Topology-Divided
Dynamic Event Scheduling (TD-DES), organizes the
wireless network into a multi-hop network tree - The root of the tree creates a data dissemination
schedule and propagates this schedule throughout
the tree - The schedule is divided into fixed-size time
slots, each indicating the type of data that are
sent (or received), and whether it is for
downstream (i.e., away from the root) or upstream
(i.e., toward the root) communication - The schedule can be periodic or refreshed in
arbitrary intervals, depending on the data
traffic and applications -- the idea is that
nodes can save energy by powering down their
radios to standby mode when they have no data to
send, and when they (and their descendants) do
not wish to receive the data being transmitted
41Power-Efficient Data Dissemination in Wireless
Sensor Networks Cetintemel 2003
- Introduction
- The system uses the publish/subscribe model each
node has a specific subscription profile that
indicates which data types the node is interested
in receiving - TD-DES allows each node to selectively listen for
interested data based on the its position in the
network topology - Since data must be scheduled before it is sent,
the main tradeoff investigated is increased power
efficiency in exchange for sub-optimal message
dissemination latency - This work addresses application-specific
scheduling and data dissemination issues, which
was not taken into consideration by the previous
in this area
42Power-Efficient Data Dissemination in Wireless
Sensor Networks Cetintemel 2003
- II. System Model
- TD-DES is intended as application overlay to a
CSMA/CA wireless MAC layer rather than a
MAC/networking layer in itself - II.A Scheduling Model
- TD-DES monitors when each node of a network (1)
receives data, (2) transmits data, and (3) powers
its radio down to a low-power standby mode - These radio modes Tx, Rx, and standby are
cycled among as functions of time determined by
the networks dissemination schedule, generated
by the root node and propagated down the tree as
part of a control event - The base station is considered to be the root
node with higher computational, storage, and
transmission capabilities than the rest of the
nodes and it can serve as an entry point to the
sensor network, integrating the sensor network
with the external wired network where the
monitoring task GUI resides
43Power-Efficient Data Dissemination in Wireless
Sensor Networks Cetintemel 2003
- II.A Scheduling Model
- The scheduler depends on topology information,
event profiles, traffic statistics, and QoS
requirements when generating dissemination
schedules - The goal of the scheduler is to minimize
network-wide power consumption (by minimizing the
amount of time spent in the Rx and Tx modes)
without sacrificing timely dissemination of data - II.B Network Model
- TD-DES has an integrated network construction
layer that organizes a wireless network into a
tree topology - The topology is constructed by broadcasting
advertisements from all nodes - First, the root node broadcasts a parent
advertisement - Each node hearing this advertisement replies with
a child message that indicates that the node will
become a child of the root
44Power-Efficient Data Dissemination in Wireless
Sensor Networks Cetintemel 2003
- II.B Network Model
- Whenever a node becomes a child, it broadcasts
its own parent advertisement - The process continues until all the nodes get
attached to the tree - A node that hears multiple parent advertisements
chooses its parent node with the lowest hop count
to the root - The tree construction layer is adaptive to
topology changes due to node failures, additions,
and mobility - The data events are disseminated throughout the
network based on per-node event description
rather than point-to-point messaging - This publish/subscribe type of event-based
communication is the data dissemination model of
choice since it decouples the producers and
consumers of information
45Power-Efficient Data Dissemination in Wireless
Sensor Networks Cetintemel 2003
- II.C Data/Event Model
- Overlaying applications define predefined event
types and these event types are maintained in a
global event schema - For instance, a network with n different event
types may publish event types e1, e2, e3,, en - Each node maintains its own event subscription
which is the set of event types that a node is
interested in as well as its own effective
subscription which is the union of its own
subscription and the subscriptions of all its
descendants - Each node subscribes to any event type of its own
interest as well as any event type of a
descendent node is interested in since each node
is responsible for forwarding all relevant events
to its descendants in the tree topology
46Power-Efficient Data Dissemination in Wireless
Sensor Networks Cetintemel 2003
II.C Data/Event Model
Figure 3 An example dissemination
tree Subscriptions are given at the upper left
corner of each node, effective subscriptions at
the upper right. Arrows indicate the links over
which the event is broadcast
47Power-Efficient Data Dissemination in Wireless
Sensor Networks Cetintemel 2003
- II.C Data/Event Model
- Figure 3 presents a dissemination tree of eight
nodes and three event types e1, e2, and e3 with
N1 being the root node of the tree - The subscription of each node is given in
parentheses at the upper left of the node and the
effective subscription is given at the upper
right of each node in square brackets - Note that an event of type e2 generated at node
N5 - The arrows indicate the links across which the
event is broadcast to disseminate the event to
all subscribing nodes - Note that the event is propagated both upstream
(to the root and then downstream to the
interested parties in the other sub-tree) and
downstream therefore, events do not always go
through the root node
48Power-Efficient Data Dissemination in Wireless
Sensor Networks Cetintemel 2003
- II.C Data/Event Model
- An event is a message type with its own unique
application-specific semantics - Consider a scenario where a sensor network whose
purpose is to detect fires is deployed over a
forested region - A sensor node may issue a fire_detected event to
the network if its temperature reading is very
high - This event would be disseminated through the
network to all those nodes, (such as forest
ranger stations, a centralized forest fire
monitoring station, or a sink node which could
notify the police, local fire-fighting units, and
public news services) subscribing to
fire_detected events - These nodes can also include any intermediate
nodes which had to forward such events to
interested nodes, even if themselves may not be
interested
49Power-Efficient Data Dissemination in Wireless
Sensor Networks Cetintemel 2003
- II.D Application-defined QoS
- Besides carrying unique type semantics, event
types may be associated with network-specific
physical characteristics, such as minimum and
maximum event payload sizes, latency constraints,
and relative event priorities - The overlaying applications specify such event
latency and priority values -
- III. Protocols
- TD-DES event schedule determines the temporal
partitioning of the RF medium for all of the
event types by allocating time slots (or slots)
for each event type - Each time slot is assumed to be wide enough for a
single event to be propagated one hop in other
words, each slot should provide sufficient time
to the underlying MAC layer to perform collision
detection and retransmissions under contention
50Power-Efficient Data Dissemination in Wireless
Sensor Networks Cetintemel 2003
- III. Protocols
- Time slots are allocated for each event based on
the determined or expected bandwidth requirements
needed to propagate all generated events reliably
throughout the network - Once the numbers of upstream and downstream time
slots for each event type are determined, the
ordering of the time slots must then be
determined - Iterations are intervals of schedule that starts
with a control event slot and it is also possible
to interleave downstream and upstream slots
together to fit into a single iteration
51Power-Efficient Data Dissemination in Wireless
Sensor Networks Cetintemel 2003
- III.A Schedule Propagation
- The root node creates a schedule of time slots
where each time slot is designated as a send or
receive slot, whether it is for upstream or
downstream communication, and by the event type
which it should be used to propagate - The schedule is created one iteration at a time
and passes it down through the dissemination tree
inside a control event - The schedule of slots between two consecutive
downstream control events is called a single
iteration of the schedule - Figure 4 presents the basic idea of creating a
schedule and passing it down the network tree
using a scenario with downstream propagation of
control and data events - The control event is created by TD-DES and
contains scheduling information
52Power-Efficient Data Dissemination in Wireless
Sensor Networks Cetintemel 2003
- III.A Schedule Propagation
- The control event is received by the node at
level X in the first time slot - In the next time slot, this node transmits the
control event down to the next level, X1. - In the following time slot, the node at level X1
passes the control event down to level X2, and
so on - Basically, iterations are delimited by control
events and can consist of a different number of
data events - The control event initiating an iteration
specifies the schedule of events within that
iteration - Note that the schedule is shifted one slot at
each level -
53Power-Efficient Data Dissemination in Wireless
Sensor Networks Cetintemel 2003
- III.A Schedule Propagation
- The schedule has a sequence of atomic send and
receive time slots, each one for a specified
event type - Generally, at a given node, for a particular
event in a schedule, time slots are allocated as
a receive slot followed by an immediate send slot
Figure 4 An example of schedule propagation
54Power-Efficient Data Dissemination in Wireless
Sensor Networks Cetintemel 2003
- III.A Schedule Propagation
- The node, if both the schedule specifies a
receive time slot for event e1 and if the node
subscribes to e1, will listen to the RF medium in
Rx mode during this time slot to receive such an
event - If the schedule specifies a send time slot for
e1, the node can transmit an event of this type - Each slot is either a downstream slot (for
parent-to-child communication away from the root)
or as an upstream slot (for child-to-parent
communication toward the root) - For downstream communication, send and receive
slots are used whereas upstream slots are not
designated for event types, as they are allocated
if any generated event may be able to make use
of the next upstream slot
55Power-Efficient Data Dissemination in Wireless
Sensor Networks Cetintemel 2003
- III.A Schedule Propagation
- Since nodes must always listen to upstream
receive slots, as all events must be passed up to
the root, regardless of event type, the unique
upstream slots for specific event types would not
be meaningful - The downstream control event includes data used
by tree construction algorithm such as the number
of hops to the root and the parent nodes
network-unique identifier - For each downstream send event, the simultaneous
time slot at the next level down is a receive
time slot for the same type of event - Similarly, for upstream send events, the
concurrent time slot at the next level up is a
corresponding receive time slot for the same type
of event
56Power-Efficient Data Dissemination in Wireless
Sensor Networks Cetintemel 2003
- III.B Deterministic and Speculative Scheduling
- TD-DES schedules time slots in two modes
deterministic and speculative where the
deterministic algorithm is used for downstream
and the speculative algorithm for upstream
dissemination - It is assumed that most event propagation would
be downstream - In the deterministic algorithm, events are
propagated in back to back iterations where each
iteration is further divided into slots of fixed
width - The scheduler (root node) knows the exact events
to be broadcast at the beginning of each
iteration and allocates the number of slots
required accordingly - The schedule is propagated to every node in the
form of a control packet at the beginning of each
iteration
57Power-Efficient Data Dissemination in Wireless
Sensor Networks Cetintemel 2003
- III.B Deterministic and Speculative Scheduling
- A control packet can also contain timing
information for the next control packet, if
iterations are not fixed length - When the root node starts transmitting events,
each node leaves radio in Rx mode for the
duration of the slot when some interesting event
will arrive - Figure 5 presents the process of deterministic
scheduling - R and S denote the receive and send slots for the
control events - Event e1 generated during iteration k cannot be
scheduled till iteration k1
- The control event transmitted during the second S
includes the schedule for iteration k1 - The exact time slot during which e1 will be
scheduled is determined by the specific ordering
criterion
58Power-Efficient Data Dissemination in Wireless
Sensor Networks Cetintemel 2003
- III.B Deterministic and Speculative Scheduling
- In speculative scheduling, the scheduler
estimates the expected frequency of event types
at the root node and pre-allocates slots based on
this frequency estimation - Since allocation of slots for each event type is
periodic which means the same from one iteration
to the next, no schedule broadcasting is needed
except when updating schedule
Figure 5 Deterministic Scheduling
59Power-Efficient Data Dissemination in Wireless
Sensor Networks Cetintemel 2003
- III.B Deterministic and Speculative Scheduling
- The drawback of speculative scheduling is that
the nodes may have to stay in Rx mode for
scheduled slots regardless of whether or not
event is coming - Figure 6 presents the process of speculative
scheduling - Event e1 is received during iteration k after its
scheduled slot (indicated by the dashed lines),
therefore, e1 needs to be queued before it can be
transmitted during its slot in iteration k1
Figure 6 Speculative Scheduling
60Power-Efficient Data Dissemination in Wireless
Sensor Networks Cetintemel 2003
- III.B Deterministic and Speculative Scheduling
- The schedule decided by the root node is known to
every node irregardless of the algorithm used - A child nodes downstream schedule is one slot
behind its parent nodes downstream schedule,
whereas a child nodes upstream schedule is one
slot ahead of the parent nodes upstream schedule - This allows tight pipelining a
downstream/upstream event received by node i in
slot t will be sent downward/upward to is
children/parent in slot t 1 - If shifting happens at the boundary of upstream
and downstream schedule, downstream scheduling
will shift beyond the neighboring upstream
schedule and similarly, upstream scheduling will
shift beyond the neighboring downstream schedule
61Power-Efficient Data Dissemination in Wireless
Sensor Networks Cetintemel 2003
- III.B Deterministic and Speculative Scheduling
- The schedule created by the root node can be
extended at an internal node to accommodate
events generated at internal nodes - Since a sub-tree rooted at an internal node may
not be interested in every event therefore, when
an internal node is propagating down root
schedule to its descendants, it can extend the
root schedule by replacing those un-interesting
slots with its own events or if more slots are
required, it can modify blank slot in the root
schedule - This extended schedule only affects the sub-tree
rooted at this internal node
62Power-Efficient Data Dissemination in Wireless
Sensor Networks Cetintemel 2003
- III.C Scheduling Criteria
- Determines how the root node decides on event
ordering in the downstream schedule - When iteration length and slot length become
fixed, a deterministic schedule becomes an
ordering of events and it is determined according
to one of (or combination of) three criteria - priority - the relative priority of an event type
over other event types - popularity - the number of nodes subscribing to
an event type - latency constraint - the max. dissemination delay
for an event type - Priorities can be specified by the
application-layer for event types at the root
node and passed down the tree within the
downstream control event - If the priorities are relatively fixed, they need
to be included in the control event in case of
new event types are added or the priorities change
63Power-Efficient Data Dissemination in Wireless
Sensor Networks Cetintemel 2003
- III.C Scheduling Criteria
- Events can also be ordered by popularity
- It is assumed that the event types that are most
subscribed to are considered most important by
the system, so they are scheduled first in the
upcoming iteration(s) - The tree-construction and maintenance layer of
TD-DES gathers the popularity of each event type
in a bottom up manner - Consider a subscription to a specific type of
event ei - Each node p maintains count(ei) indicating how
many nodes in its sub-tree are interested in this
event of type ei
64Power-Efficient Data Dissemination in Wireless
Sensor Networks Cetintemel 2003
- III.C Scheduling Criteria
- Using subscript to indicate location of the
variable, countp(ei) can be computed recursively
by -
- where 1 is for case p itself is subscribed 0
indicates otherwise - If latency constraints are specified by the
application layer, TD-DES will use the average-
and worst-case latency dissemination estimates
when scheduling events - The overall dissemination latency of an event can
be reduced by scheduling it as early as possible
reduces the scheduling delay component of the
latency
65Power-Efficient Data Dissemination in Wireless
Sensor Networks Cetintemel 2003
- III.C Scheduling Criteria
- Hop-count-based distance is used as an estimator
instead due to unavailability of real latency at
time of scheduling - The number of hops from root for a node k
subscribing to event type ei is called the
distance of ei at node k - distanceavg(ei) avg. distance for all nodes
subscribing to event type ei - distancewst(ei) the worst-case distance
- The tree gathers data by having each internal
node maintain partial values for its own sub-tree
and pass these values up to its parent node in
its upstream control event
66Power-Efficient Data Dissemination in Wireless
Sensor Networks Cetintemel 2003
- III.C Scheduling Criteria
- Each node j maintains the following metrics in
addition to count(ei), which it passes to its
parent - costj(ei) the total number of hops an event ei
must be propagated to the entire sub-tree rooted
at the current node j - avg_costj(ei) the average number of hops an
event ei must be propagated per interested node
inside the sub-tree rooted at the current node j - max_costj(ei) the maximum number of hops an
event ei must be propagated to an interested node
inside the sub-tree rooted at the current node j - Each node j passes its costj(ei) and
max_costj(ei) values to the parent as parameters
of its upstream control event
67Power-Efficient Data Dissemination in Wireless
Sensor Networks Cetintemel 2003
- III.C Scheduling Criteria
- For each child j of an internal node k, the
parent node calculates its own values
recursively the costk(ei) at k is calculated in
terms of each child -
- The maximum cost value is the maximum of the
maxima of its children plus 1 - At each node, the avg_costk(ei) is a derived
value of countk(ei) and costk(ei)
68Power-Efficient Data Dissemination in Wireless
Sensor Networks Cetintemel 2003
- III.C Scheduling Criteria
- For each child j of an internal node k, the
parent node calculates its own values
recursively the costk(ei) at k is calculated in
terms of each child - The root node, r, defines, for each event type
ei, the system-wide count and distance values in
the following way as count(ei) countr(ei), - distanceavg(ei) avg costr(ei), and
distancewst(ei) max costr(ei) - Since all internal nodes are interested in
knowing these three values, the root node
disseminates these values in a downstream control
event as they change
69Power-Efficient Data Dissemination in Wireless
Sensor Networks Cetintemel 2003
- III.D Interleaved Scheduling
- This stage determines the actual sequence of the
time slots allocated for the next iteration - The number and ordering of events in downstream
schedule and number of slots in upstream schedule
are complete - The sequencer must derive a set of ordered slots
for the next iteration from these two schedules - Two choices either place upstream and downstream
slots separately side by side (a.k.a. clustered)
or interleave them - In the clustered version, the ordered downstream
set is placed unbroken, followed immediately by
ordered upstream set and followed by some blank
time slots - A downstream control event is placed at the
beginning of each iteration
70Power-Efficient Data Dissemination in Wireless
Sensor Networks Cetintemel 2003
- Advantages
- The authors strive to achieve maximum power
conservation by way of completely powering down
the radio of the sensor nodes during the portions
of the schedule that do not match the its
particular event subscription - The authors did not try to reinvent the wheel by
introducing a radically new protocol proposed
protocol, TD-DES, is intended as an application
overlay to the already established CSMA/CA
wireless MAC layer - The publish/subscribe style of event based
communication makes the protocol well suited for
dynamic ad hoc environment
- Disadvantages
- Does not consider transmission failure
- No mentioning about the construction of the
topology tree - The time synchronization is an assumption made by
the authors
71Power-Efficient Data Dissemination in Wireless
Sensor Networks Cetintemel 2003
- Suggestions/Improvements/Future Work
- Since constructing a tree structure that is
optimal with respect to power consumption is
NP-complete, we can have the following two
heuristics - Centralized Tree-topology In this case, we can
periodically recompute the tree using centralized
incremental power heuristic, where we add on
sensor at a time with the least incremental
transmit power - Distributed Tree-topology Decision on the sensor
nodes position in the tree is done locally by
collaborating with the neighbor nodes - As mentioned in the literature, we can extend the
protocol to include upstream and downstream
aggregation and caching - Future work can be summarized as follows
- Implementation and clock synchronization
- Mobility and reliability
- Caching and aggregation
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