Topology Management

1
Topology Management Ad hoc and Sensor Networks
2
The Need for Topology Management

• What is it?
• The physical or logical interconnection pattern
  of a network
• Topology schemes in wired networks
• Bus
• Star
• Ring
• Why do we need different schemes in sensor
  networks?
• location of sensors is not deterministic
• resource constraints

3
The Need for Topology Management

• Energy/Power consumption
• Interference
• Throughput
• Connectivity

4
Motivation for Backbone Architecture
Mobility-Adaptive Protocols for Managing Large
Ad hoc Networks Basagni 2001

• essential for management of large ad hoc networks
• helps generate the minimum possible overhead for
  construction and maintenance of the backbone
  network
• can provide efficient solution for mobility and
  node/link failures in very large ad hoc networks

5
Proposed B-Protocol Description
Mobility-Adaptive Protocols for Managing Large
Ad hoc Networks

• B-Protocol
• Also known as backbone protocols
• Sets up and maintains a connected network
  (B-network)
• B-network convey the time-sensitive network
  management information
• from every node in the network with minor
  overhead and in a timely manner
• Comprises two major tasks
• (a) B-nodes selection
• (b) B-links establishment
• Nodes that are not selected as B-nodes are termed
  F- nodes that belong to the
• flat network

6
B-nodes Selection
Mobility-Adaptive Protocols for Managing Large
Ad hoc Networks

• Executed at each node based on a nodes own
  weight
• Weight is computed based on what is most critical
  to that node for the specific network application
• The highest weight of a node is more suitable to
  be a B-node
• A node knows
• Its own identifier (ID) and weight
• Ids, weights and roles (B-node or F-node) of
  one-hop neighbors
• Once a node b determines its role as B-node, all
  its neighbors may become the F-nodes served under
  b unless they have decided to join another node
• B-nodes selection is adaptive to node mobility
  and changes in its local status

7
B-nodes Selection
Mobility-Adaptive Protocols for Managing Large
Ad hoc Networks
Illustrative Example
Numbers represent node IDs and numbers within
parentheses represent the node weights
8
B-nodes Selection
Mobility-Adaptive Protocols for Managing Large
Ad hoc Networks
Illustrative Example
6(1)
2(3)
4(9)
B-node
1(6)
B-node
7(5)
3(2)
5(8)
8(1)
B-node
9
B-links Establishment
Mobility-Adaptive Protocols for Managing Large
Ad hoc Networks

• Determines the inter-B-nodes links to be
  established in order for the network to be
  connected
• Two types of B-links
• Physical when a direct link between B-nodes at
  most three hops away can be established without
  involving intermediate F-nodes (via power
  control or directional antenna)
• Virtual when a direct link between B-nodes at
  most three hops away cannot be established. In
  this case, virtual link is implemented among two
  B-nodes by a corresponding physical path with at
  most three links
• The rules stated follow the theorem proven in
  Chlamtac 96

10
B-links Establishment
Mobility-Adaptive Protocols for Managing Large
Ad hoc Networks
Theorem 1 Chlamtac 96
Given a set B of network nodes such that no two
of them are neighbors and every other node has a
link to a node in B, then a connected backbone is
guaranteed to arise if each node in B establishes
links to all other nodes in B that are at most
three hops away. Moreover, these links are all
needed for the deterministic guarantee in the
worst case, in the sense that if any of them is
left out then it is not true anymore that the
arising backbone is connected for any underlying
flat network.
11
Properties of B-protocol
Mobility-Adaptive Protocols for Managing Large
Ad hoc Networks

• Each node in flat network knows only its one-hop
  neighbors. This induces the minimum possible
  overhead
• B-link establishment is run at each B-node only
  with no knowledge of the surrounding B-nodes.
  Again, this induces the minimum overhead
• Every B-node serves a number of F-nodes each of
  which is at most three-hops away. B-node
  selection protocol guarantees that all the
  F-nodes are served by only one neighboring B-node
• There are no two B-nodes that are neighbors in
  the flat network. This guarantees that B-nodes
  are evenly distributed in the network
• B-node selection is based on the nodes current
  status (weight)

12
Properties of B-protocol
Mobility-Adaptive Protocols for Managing Large
Ad hoc Networks

• The B-network is always connected provided that
  the underlying flat network is connected
• B-protocols takes into account different
  technologies and mechanisms that can be used to
  link the B-nodes in the network. Two types of
  B-links are provided namely physical and virtual
  links. Physical links are used when there is a
  direct link between B-nodes at most three hops
  away and virtual links are used when there is a
  direct link cannot be established

13
Simulation Environment
Mobility-Adaptive Protocols for Managing Large
Ad hoc Networks

• A simulator used for an ad hoc network of nodes
  ranges 100 - 1000
• Nodes can freely move around in a rectangular
  region (a grid)
• Node movements are discretized to grid units of 1
  meter
• A node determines its direction randomly by
  choosing between its current direction (with 75
  probability) and uniformly among all other
  directions (with 25 probability)
• When a node hits a grid boundary, it bounces back
  into the region with an angle determined by the
  incoming direction
• Fixed transmission range of each node (250 m) and
  the grid size have been chosen to obtain a good
  network connectivity
• Each packet contains the time-stamped, node
  identified weight of the sending node. All
  packets are sent for the one-hop neighbors only

14
Simulation Results
Mobility-Adaptive Protocols for Managing Large
Ad hoc Networks

• k is the total number of F-nodes a B-node can
  serve at any point in time
• Three cases
• k lt n (where n is total number of nodes in
  network)
• k lt 4
• k lt 8

Figure 1 Number of B-nodes ( w.r.t the number
of the network nodes)
15
Simulation Results
Mobility-Adaptive Protocols for Managing Large
Ad hoc Networks

• k is the total number of F-nodes a B-node can
  serve at any point in time
• Three cases
• k lt n (where n is total number of nodes in
  network)
• k lt 4
• k lt 8

Figure 2 Number of B-links () when a physical
link between any two B-nodes can be established
directly.
16
Simulation Results
Mobility-Adaptive Protocols for Managing Large
Ad hoc Networks

• k is the total number of F-nodes a B-node can
  serve at any point in time
• Three cases
• k lt n (where n is total number of nodes in
  network)
• k lt 4
• k lt 8

Figure 3 Number of B-links () when a link
between B-nodes is implemented by a physical
path with at most three hops away
17
Optimizing Sensor Networks in the
Energy-Latency-Density Design SpaceSchurgers
2002

• Describes
• a topology management technique that is power
  efficient
• energy, Latency and Density trade-offs
• Provides
• a theoretical analysis of these techniques,
  including a mathematical formulation that can be
  used to design a network with required energy,
  latency and density configuration
• a hybrid solution with existing topology
  management scheme (GAF) to provide energy saving
  of over two order of magnitude
• The proposed new topology management scheme is
  called
• STEM (Sparse Topology and Energy Management)

18
Optimizing Sensor Networks in the
Energy-Latency-Density Design SpaceSchurgers
2002

• Two states for sensor nodes
• Monitoring State
• Transfer State
• Most of the time a sensor remains in monitoring
  state (i.e. sensing environment)
• When an event occurs, nodes come into transfer
  mode and transfer their data

19
Optimizing Sensor Networks in the
Energy-Latency-Density Design SpaceSchurgers
2002

• Issues
• Nodes must listen periodically for call to duty
  (i.e transfer)
• But if they poll periodically on the same
  frequency, it will collide with other data
  transfer
• Solution
• Use two radios, one for polling while the other
  for data transfer
• STEM-B (Beacon Approach)
• Initiator sends a stream of beacon packets to
  poll a target with initiator and target MAC
  addresses
• Target node sends acknowledgement on receiving
  the packet
• Target node turns its transfer radio on

20
Optimizing Sensor Networks in the
Energy-Latency-Density Design SpaceSchurgers
2002

• STEM-T (Tone Approach)
• Initiator sends a wake up tone
• Every node receiving that tone starts its data
  transfer radio
• No need to send acknowledgement
• Every node in the neighborhood of initiator wakes
  up
• STEM/GAF Hybrid
• GAF proposes a scheme in which a sensor network
  is divided in a grid
• One node in a region has its radio on, others
  have it turned off
• Nodes alternate the responsibility of being the
  active node
• GAF uses network density to conserve energy
• Assuming the active node to be the virtual node,
  STEM can be used on the virtual node to manage
  whole network

21
Optimizing Sensor Networks in the
Energy-Latency-Density Design SpaceSchurgers
2002

• Advantages
• Highly efficient in environments where events are
  rare
• Flexible in term of design trade-off for energy,
  latency and density
• Transition from monitoring state to transfer
  state is easily achieved
• No synchronization required
• Can be use with other topology management schemes
  like GAF
• Disadvantages
• Continuous polling consumes energy
• Not suitable for highly reactive environments
• Requires extra radio on sensor nodes
• Suggestions/Improvements/Future Work
• Analysis of STEM with clustered networks

22
ASCENT Adaptive Self-Configuring sEnsor Networks
Topologies Cerpa 2002

• In ASCENT, the nodes coordinate to exploit the
  redundancy provided by high density to extend the
  overall system lifetime
• Nodes achieve self-configuration to establish a
  topology that provides communication and sensing
  coverage under energy constraints
• Each node examines its connectivity and adapts
  its participation in the multi-hop network
  topology based on the operating region
• The node
• Signals when it detects high message loss,
  requesting additional nodes to join the network
  to continue relaying messages
• Reduces its duty cycle if high messages losses
  are detected due to collisions
• Probes local communication environment and only
  joins to the multi-hop routing infrastructure if
  it is useful

23
ASCENT Adaptive Self-Configuring sEnsor Networks
Topologies Cerpa 2002

• Sensor nodes do local processing to reduce
  communication and energy costs
• Challenges arises from the increased level of
  dynamics (systems and environmental)
• One of the most important challenge arises from
  energy constraints imposed by unattended systems
• These systems must be long-lived and operate
  without manual intervention
• They need to self-configure and adapt to
  environmental dynamics and some terrain
  conditions may result regions with non-uniform
  communication density
• These issues can be addressed by deploying
  redundant nodes and designing algorithms to use
  redundancy to extend the system lifetime
• Scaling challenges are associated with spatial
  coverage and robustness
• Central vs. Distributed
• When energy is constraint and environment is
  dynamic, distributed approaches are preferable
  and practical

24
ASCENT Adaptive Self-Configuring sEnsor Networks
Topologies Cerpa 2002

• Scalable wireless sensor networks require to
  avoid large amounts of data being transmitted
  over long distances
• ASCENT applies well-known techniques from MAC
  layer protocols to the problem of distributed
  topology formation
• Imagine a habitat monitoring sensor network that
  is deployed in remote forest
• The deployed systems must confer with the
  following conditions
• Ad-hoc deployment
• Energy constraints
• Unattended operation under dynamics
• If we use too few nodes initially
• the distance between neighboring nodes will be
  too far
• packet loss rate may increase
• energy required to transmit over larger distances
  may be prohibitive

25
ASCENT Adaptive Self-Configuring sEnsor Networks
Topologies Cerpa 2002

• If we use all deployed nodes simultaneously
• system will expand unnecessary energy
• nodes interfere with each other by congesting the
  channel
• ASCENT does not use localized distributed
  algorithm to find a single solution
• Adaptive self-configuration using localized is
  suited to problem spaces which have a vast number
  of possible solutions (in this case, large
  solution spaces means dense node deployment)
• ASCENT has the following two assumptions
• Carrier Sense Multiple Access (CSMA) MAC protocol
• Possibilities for resource contention when too
  many neighboring nodes participate in the
  multi-hop network
• Reacts when links have high packet loss
• Does not detect or repair network partitions and
  assumes that there is enough node density to
  connect the entire region

26
ASCENT Adaptive Self-Configuring sEnsor Networks
Topologies Cerpa 2002

• Two essential contributions of ASCENT design are
• Adaptive techniques that allow applications to
  configure the topology based on the needs while
  saving energy to extend network lifetime. The
  techniques do not assume a specific model or
  fairness, degree of connectivity, or capacity
  required
• Self-configuring techniques that react to
  operating conditions are measured locally. It
  does not assume any specific radio propagation
  model, geographical distribution of nodes, or
  routing mechanisms used
• ASCENT Design
• Adaptively elects active nodes from all the nodes
• Active nodes stay awake always and participate in
  routing while the other nodes remain passive and
  periodically checks if they should become active

27
ASCENT Adaptive Self-Configuring sEnsor Networks
Topologies Cerpa 2002

• ASCENT Design
• Initially, only some nodes are active while other
  are passively listening to packets but not
  transmitting
• When source starts transmitting data packets
  towards the sink, the sink gets high message loss
  from the source due to limited radio range,
  called communication hole
• The receiver gets high packet loss due to poor
  connectivity with the sender

Figure 2(a) Communication Hole
28
ASCENT Adaptive Self-Configuring sEnsor Networks
Topologies Cerpa 2002

• ASCENT Design
• Sink start sending help messages to neighbors
  that are in listen-only mode, called passive
  neighbors, to join the network
• When a neighbor receive a help message, it
  decides to join the network or not
• If the node joins, it becomes an active neighbor
  and signals the existence of a new active
  neighbor to other passive neighbors by sending a
  neighbor announcement message
• It continues until the number of active nodes
  stabilizes on a certain value and the cycle stops

29
ASCENT Adaptive Self-Configuring sEnsor Networks
Topologies Cerpa 2002

• ASCENT Design
• When the process is completed, the newly joined
  nodes participate in the data delivery process
  from source to sink more reliably
• The process will be repeated in the case of
  network event (e.g., node failure) or
  environmental effect (e.g., new obstacle) causes
  message loss

Figure 2(b-c) Self-configuration transition and
final state
30
ASCENT Adaptive Self-Configuring sEnsor Networks
Topologies Cerpa 2002
ASCENT State Transactions
NT neighbor threshold LT loss threshold T?
state timer values (p passive, s sleep, t
test) DL Data loss rate
31
ASCENT Adaptive Self-Configuring sEnsor Networks
Topologies Cerpa 2002

• ASCENT State Transactions
• Initially, a random timer turns on the nodes to
  avoid synchronization
• Node initializes to test state
• Sends data and routing control messages
• Sets up a timer, Tt and sends neighbor
  announcement messages
• Moves into passive state if the conditions are
  met before Tt expires
• When Tt expires, it enters to active state
• The reasoning behind the test state is to probe
  the network to decide whether the addition of a
  new node would improve connectivity
• On entering the passive state, node
• Sets up a timer Tp and when Tp expires, it enters
  to sleep state
• If before Tp expires, it enters to test state
  only if the conditions are met
• Nodes in passive state can hear all packets
  transmitted, but no routing or data packets are
  forwarded in this state since this is listen-only
  state

32
ASCENT Adaptive Self-Configuring sEnsor Networks
Topologies Cerpa 2002

• ASCENT State Transactions
• The reasoning behind the passive state is to
  gather information about the state of the network
  without causing interference with other nodes
• Nodes in passive and test states update the
  number of active neighbors and data loss rates
• In passive states, the nodes still consume energy
  since the radio is on
• The nodes in sleep state turns the radio off,
  sets up timer Ts and goes to sleep
• When Ts expires, the nodes moves into passive
  state
• A node in the active state continuous to forward
  data and routing packets until it runs out of
  energy

33
ASCENT Adaptive Self-Configuring sEnsor Networks
Topologies Cerpa 2002

• ASCENT Parameters Tuning
• ASCENT has many parameters and the choices are
  left to the applications such as a particular
  application may trade energy savings for greater
  sensing coverage
• Neighbor Threshold (NT)
• Determines the average connectivity if the
  network
• Tradeoff between energy consumed and/or level of
  interference (packet loss) vs. desired sensing
  coverage
• Loss Threshold (LT)
• Determines the maximum amount of data loss an
  application can tolerate before requesting help
  to improve network connectivity
• This value is highly application dependent

34
ASCENT Adaptive Self-Configuring sEnsor Networks
Topologies Cerpa 2002

• ASCENT Parameters Tuning
• Test timer (Tt), Passive timer (Tp), Sleep timer
  (Ts)
• Determines the maximum time a node remains in
  test, passive, sleep states
• Tradeoff between power consumption vs. decision
  quality

35
SPAN An Energy-Efficient Coordination Algorithm
for Topology Maintenance in Ad hoc Wireless
Networks Chen 2002

• SPAN is a power saving technique for multi-hop ad
  hoc networks that reduces energy consumption with
  the consideration of maintaining the capacity or
  connectivity of the network
• It is distributed and randomized algorithm in
  which the nodes make local decisions on whether
  to sleep or join to the backbone
• Each node decides based on an estimate of how
  many neighbors will benefit from it being awake
  and the energy available to it
• Improvement in the system lifetime increases
  along with the ratio of idle-to-sleep energy
  consumptions
• Non-coordinators remain in power saving mode and
  periodically check to see if they should wake up
  and become coordinators

36
SPAN

• A good power saving technique for ad hoc networks
  should have the following
• Allow as many as nodes to turn their radios off
  most of the time
• Forward packets between any source and
  destination with the minimum possible delay than
  if all nodes were awake
• Distributed algorithm where having each node
  making local decisions
• Backbone formed by the awake nodes should provide
  close to total capacity as the original networks
  such that congestion can be avoided
• Do not make many assumptions about the link
  layers facilities for sleeping and work with any
  link layer that provides sleeping and periodic
  polling
• Inter-operate correctly with any routing
  algorithm being used
• SPAN fulfills all the above requirements
• Each node makes periodic local decisions to sleep
  or stay awake as a coordinator and participate in
  the forwarding backbone topology

37
SPAN

• In order to keep the same level of capacity of
  the original network, a node may volunteer to
  become a coordinator if it figures out from the
  local information gathering that two of its
  neighbors cannot communicate directly or through
  one or two existing coordinators
• In order to keep the number of coordinators low
  and rotate this role amongst all nodes, each
  node delays sending message about its desire to
  become a coordinator by a random time interval
• The decision is based on two factors
• the remaining battery energy
• the number of pairs of neighbors it can connect
  together
• This allows SPAN to maintain capacity-preserving
  backbone at any time with the nodes consuming
  about the same level of energy
• SPAN also scales well with the number of nodes

38
SPAN

• SPAN Design
• The goals of SPAN includes
• Ensures enough coordinators to be elected such
  that each node is in radio range of at least one
  coordinator
• Rotates coordinators to ensure that all nodes
  provides equal support to achieve global
  connectivity
• Increases the network lifetime, preserves the
  capacity with minimum latency by minimizing the
  number of elected coordinators
• Coordinators are elected based on local available
  information
• SPAN is proactive such that each node
  periodically broadcasts HELLO messages which
  contains the nodes status (coordinator or not),
  its current coordinators, and its current
  neighbors
• From these HELLO messages, each node keeps tracks
  of a list of the nodes neighbors and
  coordinators, and for each neighbor, a list of
  its neighbors and coordinators

39
SPAN

• Coordinator Announcement
• Each non-coordinator node periodically determines
  whether it should become a coordinator or not
• The coordinator eligibility rules ensures that
  the network is covered with sufficient number of
  coordinators
• Coordinator Eligibility Rule
• A non-coordinator node should become a
  coordinator if it figures out from the local
• information gathering that two of its neighbors
  cannot communicate directly or through
• one or two existing coordinators
• If many nodes are willing to become coordinators,
  SPAN solves this contention by delaying
  coordinator announcement with a randomized
  backoff delay
• Each node selects a delay value and delays
  sending HELLO message indicating the desire to
  become coordinator for that amount of time
• At the end of the delay, the node reevaluates its
  eligibility based on the HELLO messages received
  from neighbors and if it is still eligible, it
  makes announcement

40
SPAN

• Coordinator Announcement
• At the end of the delay, the node reevaluates its
  eligibility based on the HELLO messages received
  from neighbors and if it is still eligible, it
  makes announcement
• Consider a case where all the nodes have the same
  level of energy which means that only topology is
  considered in the decision of becoming a
  coordinator
• Consider a case where the nodes have unequal
  energy left
• Er energy remaining at node Ni number of
  neighbors for node i
• Em maximum amount of energy T round-trip
  delay for packet
• Ci number of new connections through node i R
  random number in 0, 1

Eq. 1
Eq. 2
41
SPAN

• Coordinator Announcement
• In Eq. 1, if nodes with high Ci become
  coordinators, total number of coordinators needed
  would be less to ensure that every node in the
  network is covered
• Therefore, the nodes with a high Ci values should
  volunteer for coordinator position quicker than
  those with smaller Ci
• In Eq. 2, the node with large value of (Er/Em) is
  expected to volunteer quicker to become a
  coordinator than the nodes with smaller ratio in
  order to assure the fairness

42
SPAN

• Coordinator Withdrawal
• Each node periodically checks whether it should
  withdraw as a coordinator
• A node withdraws if all of its neighbors can
  reach each other directly or with one or more
  coordinators
• For fairness, after some period of time, a
  coordinator withdraws and declares itself as a
  tentative coordinator if all neighbors can reach
  each other via other neighbors, even if these are
  not coordinators (allows neighbors to act as
  coordinators)
• A tentative coordinator is still used to forward
  packets and described coordinator announcement
  algorithm treats tentative coordinators as
  non-coordinator nodes
• A coordinator nodes gives its neighbors the
  opportunity to become coordinators by declaring
  itself as tentative coordinator
• A coordinator maintains its position as tentative
  for WT time, where WT is the maximum value of Eq.
  2 which is
• WT 3 x Ni x T

43
SPAN

• Coordinator Withdrawal
• If the coordinator has not withdrawn within WT
  time period, it clears its tentative bit
• In order to prevent node to drain its battery
  completely, the amount time a node acts as a
  coordinator before turning on its tentative bit
  is proportional to the amount of energy it has,
  indicated as (Er/Em)

44
Simulation Results
SPAN
45
Distributed Topology Control in Wireless Sensor
Networks with Asymmetric Links Liu 2003

• Topology Control
• Does not describe a new topology
• Provides a mechanism to build certain topology
• Distributed
• No central control or central source of
  information
• Asymmetric Links
• Due to the presence of heterogeneous devices

46
Distributed Topology Control in Wireless Sensor
Networks with Asymmetric Links Liu 2003

• Objective
• Reachability between any two nodes is guaranteed
  to be like initial topology
• Nodal power consumption is minimized

47
Distributed Topology Control in Wireless Sensor
Networks with Asymmetric Links Liu 2003

• Model
• Network of heterogeneous sensors (called nodes)
• Nodes deployed in a two dimensional plane
• Each node equipped with omni-directional antenna
  with adjustable transmission power
• Nodes have different maximum power
• Pi Transmission Power of Node i
• Pimax Maximum Transmission Power of Node i
• Pij Transmission Power required for node i to
  reach j
• Lij Asymmetric link from i to j
• G (V, L) directed graph of topology with max
  power
• G is strongly connected

48
Distributed Topology Control in Wireless Sensor
Networks with Asymmetric Links Liu 2003

• Algorithm
• Fully distributed with no synchronization
  required
• Takes G as input and produces G where G has
• Same bi-directional reachability
• Consumes minimum power
• Phases
• Establishing the vicinity topology
• Deriving the minimum power vicinity tree
• Propagation of transmission powers
• Optimizations

49
Distributed Topology Control in Wireless Sensor
Networks with Asymmetric Links Liu 2003

• Establishing the vicinity topology
• Node i broadcasts initialization request (IRQ)
  with Pimax
• Vi is the set of nodes that receive the message
  i.e. locationi, Pimax
• Each node j in Vi sends initialization reply
  (IRP) message i.e. locationj, Pjmax
• If Pjmax gt Pij , j can reach I with single hop
  Lji
• Otherwise find a multi-hop path to reach i
• Given the knowledge of location and max power of
  itself and all vicinity nodes, node i can
  determine the vicinity edges
• Node i establishes a vicinity topology , Gi (Vi,
  Ei)

50
Distributed Topology Control in Wireless Sensor
Networks with Asymmetric Links Liu 2003

• Deriving Minimum Power Vicinity Tree
• Derive Minimum power path in Gi, to reach from a
  node i to node j using Dijkstra or Bellman-Ford
  algortihms based on sum of power consumption on
  that path.
• Compute it for each node in Vi to obtain
  minimum-power vicinity tree,
• Gis (Vi, Eis)

51
Distributed Topology Control in Wireless Sensor
Networks with Asymmetric Links Liu 2003

• Propagation of transmission powers
• Node i computes minimum power requirement for
  itself and others nodes in Vi
• Node i sends a power request (PR) message to each
  node in Vi, describing the minimum power required
  for that node to reach farthest hop
• A node j in Vi, receiving the PR message
  increases its power requirement if the requested
  power in PR is greater than current one
• Otherwise, it discards the PR message

52
Distributed Topology Control in Wireless Sensor
Networks with Asymmetric Links Liu 2003

• Optimizations
• Achieved via discarding PR messages when
• A node already has run the algorithm to find its
  shortest vicinity tree
• A node receives a PR message for a node in its
  vicinity
• Example A asks B for PBC while B already has PBD
  to reach node C

Figure 1 A scenario of further optimized nodal
transmission range
53
Distributed Topology Control in Wireless Sensor
Networks with Asymmetric Links Liu 2003

• Advantages
• Guarantees same bi-directional interconnection
  while reducing per node power consumption
• Distributed algorithm
• No synchronization required
• No central control node with network information
• Easy to add/remove nodes from the network
• Uses existing well known algorithms to obtain
  minimum power consumption
• Works on network with asymmetric links, which
  seem more realistic
• Assumption of asymmetric links, makes it possible
  to obtain minimum power path via multi-hop rather
  than using a single hop high power link

54
Distributed Topology Control in Wireless Sensor
Networks with Asymmetric Links Liu 2003

• Disadvantages
• Computationally expensive to be run on network
  with mobile sensors
• Overhead of sending IRQ, IRP and RP in a large
  network of sensors
• Time to converge for the algorithm is large
• Suggestions/Improvements/Future Work
• More details on how multi-hop paths will be
  discovered
• Detailed example covering more complex scenarios

55
Optimal Local Topology for Energy Efficient
Geographical Routing in Sensor NetworksMelodia
2004

• The primary design constraints of the sensor
  network algorithms and protocols are
  energy-efficiency, scalability and localization
• The improved energy efficiency can be achieved by
  designing protocols and algorithms with
  cross-layer approach, i.e., considering
  interactions between different layers of the
  communication process such that overall energy
  consumption is minimized
• A scalable algorithm performs well in a large
  network
• The scalability for an algorithm is related to
  that of localization in a scalable algorithm
  each node exchanges information only with its
  neighbors (localized information exchange) in a
  very large wireless network

56
Optimal Local Topology for Energy Efficient
Geographical Routing in Sensor NetworksMelodia
2004

• This paper considers the interaction between
  topology control and energy efficient
  geographical routing
• The question to answer is How extensive should
  be the Local Knowledge of the global topology in
  each sensor node, so that an energy efficient
  geographical routing can be guaranteed?
• This question is related to the degree of
  localization of the routing scheme
• If each sensor node have the complete knowledge
  of the topology, it could compute the global
  optimal next hop to minimize the energy
  consumption
• However, the knowledge of complete topology
  information has an associated cost, i.e., energy
  used to exchange the signaling traffic

57
Optimal Local Topology for Energy Efficient
Geographical Routing in Sensor NetworksMelodia
2004

• An analytical framework is developed to capture
  the tradeoff between the topology information
  cost, which increases with the Knowledge Range of
  each node, and the communication cost, which
  decreases when the knowledge becomes more
  complete
• This analytical framework is then applied to
  different position based forwarding schemes and
  demonstrated by using Monte Carlo simulations
  that a limited knowledge is sufficient to make
  energy efficient routing decisions
• A neighbor for a certain sensor node is another
  node which falls into its topology Knowledge
  Range, denoted as KR

58
Optimal Local Topology for Energy Efficient
Geographical Routing in Sensor NetworksMelodia
2004

• The contributions of this work are
• Introduction of a novel analytical framework to
  evaluate the energy consumption of geographical
  routing algorithms for sensor networks
• Integer Linear Programming (ILP) formulation of
  the topology Knowledge Range optimization problem
• Detailed comparison of the leading existing
  forwarding schemes Takagi 1984, Hou , Finn
  1987, Kranakis 1999, Nelson 1984 and
  introduced a new scheme called Partial Topology
  Knowledge Forwarding (PTKF)
• Introduction of PRobe-bAsed Distributed protocol
  for knowledge rAnge adjustment (PRADA) for the
  on-line solution of the problem that allows nodes
  to select near-optimal Knowledge Ranges in a
  distributed way

59
Optimal Local Topology for Energy Efficient
Geographical Routing in Sensor NetworksMelodia
2004

• Advantages
• No need for knowing the global topology of the
  network
• PRADA can be run independently in the nodes, thus
  the nodes do not require time synchronization
• Demonstrates a limited amount of topology
  knowledge is sufficient in order for energy
  conserving routing protocols to be implemented
• The nodes periodically update their knowledge
  range, thus the algorithm could be implemented
  in sensor networks where the nodes are mobile
• Draws a fine line between topology information
  cost and communication cost

60
Optimal Local Topology for Energy Efficient
Geographical Routing in Sensor NetworksMelodia
2004

• Disadvantages
• No mentioning about the sensitivity towards
  location error of their proposed protocol
• For a pair of source-destination path, the most
  optimal path is always chosen however, this
  would lead to a starvation of some of the nodes
  that would not get any traffic
• The performance evaluation of protocol does not
  consider the lower layers, such as MAC

61
Optimal Local Topology for Energy Efficient
Geographical Routing in Sensor NetworksMelodia
2004

• Suggestions/Improvements/Future Work
• Extending the optimization objectives to include
  not only power but also battery level of each
  node (thus improving network lifetime)
• Implementing the proposed routing protocol within
  a simulator which considers routing and MAC layer
  together to draw a more convincible conclusion

62
References

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