Mobile Ad Hoc Network Security (MANET)

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Mobile Ad Hoc Network Security (MANET)

• Preethi Vishwanath
• San Jose State University
• Computer Science

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Definition

• A "mobile ad hoc network" (MANET) is an
  autonomous system of mobile routers (and
  associated hosts) connected by wireless links
  --the union of which form an arbitrary graph.
• The routers are free to move randomly and
  organize themselves arbitrarily thus, the
  network's wireless topology may change rapidly
  and unpredictably.
• Such a network may operate in a standalone
  fashion, or may be connected to the larger
  Internet.
• Sensor nodes consist of sensing, data
  processing, and communication components and
  typically form ad hoc networks.
• Due to a lack of infrastructure support, each
  node acts as a router, forwarding data packets
  for other nodes.
• Can be classified into two
• Server Contain the complete DBMS and bear
  primary responsibility for data broadcast and
  satisfying client queries.
• Clients Have sufficient resources to cache
  portions of the database as well as storing some
  DBMS query and processing modules.
• Practical Use Whenever a temporary network
  with no infra structure needed.
• Rescue situations Rescue workers engaged in
  disaster relief investigate the extent of the
  damage around them and collaboratively work by
  sharing the information on their locations and
  findings.
• Excavations Members of a research project team
  engaged in an archeological excavation collect
  various phenomenal data from sensors and share
  the obtained data with other members to
  streamline work.

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Criteria node to be part of a network

• To be connected to a network, a node should must
  be within the area of influence of at least one
  node on the network.
• A node with no remaining power, or one that is
  off, is not currently a part of the network.
• Even if the source and the destination nodes are
  not within each others communication range, data
  packets are forwarded to the destination by
  relaying transmission through other nodes that
  exist between the two nodes.

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Large Scale On Demand ModelRxW (request Time
Waits)

• At each broadcast tick, the server chooses an
  item to broadcast based on the number of request
  and the amount of time the original result has
  been waiting.
• The overhead for large databases is significant
  in both time and space.
• Improvements
• Approach 1 ( Guo, et. Al)
• Server maintains a list of popular or less
  popular items.
• The popular items are continuously broadcast.
• If a less popular item is needed, a client may
  request it.
• This interrupts the broadcast, which continues
  with the data broadcast after serving the
  request.
• The server never stops broadcasting, consuming
  power.
• Approach 2 ( Yajima et. Al and Grassi)
• Improve database service by the organization and
  use of the broadcast.
• Highly correlated items are found together in the
  broadcast, minimizing the number of times a
  client must access the broadcast.
• Uses prefetching related items into the client
  cache so that they will be available locally if
  needed.
• While prefetching may shorten the time a client
  needs to access a data item, prefetching wastes
  power and space through accessing and storing
  broadcast items that may not be needed.

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Algorithm 1 to handle data push and data pull
Adaptive broadcast scheduling algorithm

• Two potential ways to construct a broadcast.
• New items may be either added to the algorithm or
  may replace less important data items.
• A global network where all servers in a region
  know the location and power of all other servers
  in the region and full replication of the
  database is assumed.
• Periodically, each server broadcasts its location
  and power level. This begins the broadcast cycle
  9. This is a soft real-time system.
• There are deadlines for data delivery. The
  deadlines were used to determine which data
  request to service although no penalty for
  missing a deadline was mentioned.
• There is a leader protocol that selects the
  server in a region with the greatest remaining
  power.
• The leader coordinates the broadcast
  responsibilities of other servers in its area of
  influence.
• The lead server determines which portion of a
  broadcast each server transmits.
• The power level of each server drives this
  broadcast assignment.
• The server with the least power transmitted the
  most important data items.
• Disadvantage
• Initial algorithm has a potentially large
  communication overhead, servers with no clients
  still broadcast.
• Less popular items may be starve or be broadcast
  too late.

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Algorithm 2 to handle data push and data pull

• Utilizes a popularity factor (PF).
• The PF is a measure of the importance of a data
  item.
• The PF increases each time a request is made for
  a data item. The amount of time since the request
  was made also affects the PF.
• If it has been too long, the need to broadcast
  the item may be gone.
• This factor is called the Resident Latency (RL)
  and is system and scenario specific. The PF
  decreases whenever a request exceeds the RL
  value.
• The PF is used to assist in the building of
  relevant broadcasts and includes RL in order to
  make allowances for the movement of nodes.
• When the PF of broadcast items is high, the
  probability of a broadcast that serves maximum
  needs increases.
• If a server has not received any requests for a
  certain number of broadcasts, it will sleep
  rather than broadcast to an empty audience.
• Finally, to localize data delivery, the lead
  server assigns each server the amount of data to
  broadcast but not the items to broadcast.
• To deal with insufficient power levels, the
  servers rebroadcast the previous index and
  broadcast if they have insufficient power to
  build a new broadcast.
• Disadvantages
• Servers can be assigned a broadcast larger than
  their power levels would permit.
• Power and bandwidth is also wasted with
  duplication.

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Data replication Data correlation

• MANETs are often constructed to support
  cooperative work in environments without network
  infrastructures.
• Data replication might cause a situation whereby
  a node requests two correlated data items at the
  same time although it can access only one of
  them.
• If this situation frequently occurs, the data
  accessibility of the whole system deteriorates.
• In a real environment, the correlation among data
  items can be usually known by recording the
  access log at each node and periodically
  estimating it.
• Three replication allocation methods (proposed by
  1)
• SAF (Static Access Frequency) Only the access
  frequency to each data item is taken into
  account.
• DAFN (Dynamic Access Freq. and Neighborhood) The
  access frequency to each data item and the
  neighborhood among nodes are taken into account.
• DCG (Dynamic Connectivity based Grouping) The
  access frequency to each data item and the whole
  network topology are taken into account.

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SAF method

• Each mobile host allocates replicas of N data
  items in descending order of the access
  frequencies.
• At the time of replica allocation, a mobile host
  may not connect to another mobile host which has
  an original or a replica of a data item that the
  host should allocate. In this case, the memory
  space for the replica is retained free.
• The replica is created when a data access to the
  data item succeeds or when the mobile host
  connects to another mobile host which has the
  original or the replica at a relocation period.
• In the SAF method, mobile hosts do not need to
  exchange information with each other for replica
  allocation.
• Moreover, replica relocation does not occur after
  each mobile host allocates all necessary
  replicas.
• Advantage
• allocates replicas with low overhead and low
  traffic.
• Disadvantage
• Since each mobile host allocates replicas based
  on only the access frequencies to data items,
  mobile hosts with the same access characteristics
  allocate the same replicas.
• However, a mobile host can access data items or
  replicas held by other connected mobile hosts,
  and thus it is more effective to share many kinds
  of replicas among them.
• Gives low data accessibility when many mobile
  hosts have the same or similar access
  characteristics.

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DAFN method

• The DAFN method eliminates the replica
  duplication among neighboring mobile hosts.
• First, this method preliminary determines the
  replica allocation in the same way as the SAF
  method.
• Then, if there is replica duplication of a data
  item between two neighboring mobile hosts, a
  mobile host with lower access frequency to the
  data item changes the replica to another replica.
  
• Since the neighboring status changes as mobile
  hosts move, the DAFN method is executed at every
  relocation period.
• At a relocation period, a mobile host may not
  connect to another mobile host which has an
  original or a replica of a data item that the
  host should allocate. In this case, the memory
  space for the replica is temporary filled with
  one of replicas that have been allocated since
  the previous relocation period but are not
  currently selected for allocation. This temporary
  allocated replica is chosen among the possible
  replicas where the access frequency to the
  replica (data item) is the highest among them. If
  there is not a possible replica to be temporary
  allocated, the memory space is retained free.
  When a data access to the data item whose replica
  should be allocated succeeds, the memory space is
  filled with the proper replica.
• Advantage
• Data accessibility is expected to be higher than
  that in the SAF method.
• Disadvantage
• Does not completely eliminate replica duplication
  among neighboring hosts because it only executes
  the elimination process by scanning the network
  once based on the breadth first search.
• if the network topology changes during the
  execution of this method, the replica relocation
  cannot be done at mobile hosts over disconnected
  links
• Both the overhead and the traffic are higher than
  the SAF method because at each relocation period,
  mobile hosts exchange information and relocate
  replicas.

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DCG Method

• The DCG method shares replicas in larger groups
  of mobile hosts than the DAFN method that shares
  replicas among neighboring hosts.
• In order to share replicas effectively, each
  group should be stable, i.e., the group is not
  easily divided due to changes of network
  topology.
• From this viewpoint, the DCG method creates
  groups of mobile hosts that are biconnected
  components1 in a network. Here, a biconnected
  component denotes a maximum partial graph which
  is connected (not divided) if an arbitrary node
  in the graph is deleted.
• By grouping mobile hosts as a biconnected
  component, the group is not divided even if one
  mobile host disappears from the network or one
  link is disconnected in the group, and thus it is
  considered that the group has high stability.
• At a relocation period, a mobile host may not
  connect to another mobile host which has an
  original or a replica of a data item that the
  host should allocate.
• In this case, in the same way as the DAFN
  method, the memory space for the replica is
  temporary filled with another replica, and it is
  filled with the proper one when a data access to
  the corresponding data item succeeds.
• Advantage
• Since many kinds of replicas can be shared, the
  data accessibility is expected to be higher.
• Disadvantage
• However, since the DCG method consists of three
  steps (i) broadcasting host identifiers, (ii)
  determining the replica allocation, and (iii)
  notifying it to all hosts in the group, this
  method takes the largest time among the three
  methods to relocate replicas.

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Access to Global State Information

• Update Diffusion
• Sensed changes cause updates to be propagated to
  a database, which is typically replicated over a
  number of nodes.
• Entire state information is stored in the
  database
• Applications access an available database copy
  for state retrieval.
• Disadvantages
• Danger of inconsistencies
• Paper 10 has derivation of few algorithms which
  help in taking care of this problem.

• Query diffusion
• State information only stored in the nodes where
  it has been sensed.
• For state retrieval an application broadcasts or
  geocasts a query specifying the requested state
  information
• State information matching the query is sent back
  to the application
• Disadvantages
• For partitioned networks the availability of
  state information is poor since each state item
  is stored on a single node only
• Applications need to learn about state changes as
  fast as possible.

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References

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