Power Aware Routing in Mobile Ad-Hoc Networks

31st Oct, 2002 Power Aware Routing in Mobile Ad-Hoc Networks Sumit I Eapen - Joy Ghosh

Contents Introduction Metrics for power awareness Routing Protocols > Power SourceRouting (PSR) > Local Energy Aware Routing (LEAR) > Geographical and Energy Aware Routing (GEAR) > Minimum Energy Mobile Wireless Networks > Low Energy Adaptive Clustering Hierarchy (LEACH) > Sensor Protocols for Information via Negotiation > Hierarchical Power Aware Routing in Sensor Networks References

Introduction – Power Concerns • The lifetime of a network is defined as the time it takes for a fixed percentage of the nodes in a network to die out. • Portability of wireless nodes being critical its almost mandatory to keep the battery sizes to a bare necessary • Since battery capacity is thus fixed, a wireless mobile node is extremely energy constrained • Hence all network related transactions should be power aware to be able to make efficient use of the overall energy resources of the network

Traditional routing metrics • Aims to minimize hop counts and propagation delay • Fails to take into account the power usage of nodes • Results in poor lifetime of networks

Power Aware Metrics Intuition conserve power and share cost of routing packets to ensure increase in life of node and network Metrics 1. Minimize energy consumed / packet 2. Maximize time to Network Partition 3. Minimize variance in node power levels 4. Minimize cost / packet 5. Minimize maximum node cost

1. Minimize energy consumed / packet Definitions: • T(a,b) = energy consumed in transmitting and receiving one packet over one hop from a to b • ej = Σk-1i=1 T(ni, ni+1) = total energy spent for packet j Goal: • Minimize ej for all packets j Note: • In lightly loaded networks this automatically finds shortest hop path • In heavily loaded networks due to contention it might not be shortest

2. Maximize time to network partition Definition: • Cut Set: set of nodes that divide the network into two partitions As soon as one node in the set dies the delay experienced increases Goal: - To balance load of the nodes in the Cut Set to maximize network life Problems: • The problem is similar to scheduling tasks to multiple servers so that the response time is minimized, which is known to be NP-complete

3. Minimize variance in node power levels Goal: • To keep all nodes up and running together for as long as possible Concept: • Build a route that takes into account the amount of data waiting to be transmitted in all the intermediate nodes Merit: • Achieve some kind of load balancing to ensure similar rates of dissipation of energy throughout the network

4. Minimize cost / packet Definition: Total cost of sending packet j: cj = Σk-1i=1 fi (xi) Where, • xi is the energy dissipated in node i till now • fi(xi ) is the cost of node i: fi(xi) = 1 / (1 – g(xi)) Where g(xi) is the normalized battery capacity Goal: - Minimize cj for all packets j

4. Minimize cost / packet (contd.) Advantage: - The remaining batter power level is incorporated into the routing decision • This also balances load by avoiding usage of weak nodes in presence of stronger ones • Network congestion can be taken care of by increasing node cost in presence of contention.

5. Minimize maximum node cost Definition: • Ci(t) = cost of routing a packet through node i at time t • Ĉ(t) = maximum of the Ci(t)’s Goal: - Minimize Ĉ(t), for all t > 0 Side effects: • Delays node failure • Reduces variance in node power levels

MANET Routing Protocols Broad Classifications: • Proactive Protocols • Table Driven • Frequent topology updates • Each node knows about all destinations • Distance Vector, Link State Routing, etc. • Reactive Protocols • On Demand • A node learns of other nodes through actual communications • DSR, AODV, etc

Low Power Routing - I • Transmission Power • P (i, j) is the Link Cost defined as the power expended for transmitting and receiving a packet between two consecutive nodes i and j • Minimize Σi,jЄpath P (i, j) • Fixed transmit power • P(i,j) = b x packet_size + c Where b = packet size dependent energy consumption And c = fixed cost for MAC layer control negotiation • Varying transmit power • P(i,j) = k x dαij Where dij = distance between i and j And α = parameter depending on physical environment

Low Power Routing - II • Remaining Battery Power • Ri(t) is the remaining power of node i at time t • Simple Approach • Minimize ΣiЄpath1/Ri(t) • Min-Max Approach • Avoid routes with nodes having minimum battery capacity among all nodes in all possible routes • Conditional Min-Max Approach • Till all nodes in route have energy above a threshold, choose route with minimum total transmission power • As energy falls below threshold, use the min-max algorithm suggested above

Power-Aware Source Routing (PSR) • This is a Reactive (On demand) protocol based on DSR • Cost Function • The cost of route π at time t is C (π,t) • C (π,t) = ΣiЄπCi(t) • where Ci(t) is the cost of node i at time t • Ci(t) = ρi . [Fi/ Ri(t)]α • ρi : transmit power of node i • Fi : full-charge battery capacity of node i • Ri(t) : remaining battery power of node i at time time t • α : a positive weighting factor • This Cost function takes into account both transmission power and remaining battery power

PSR – Route Discovery • RREQ broadcast initiated by source • Intermediate nodes can reply to RREQ from cache as in DSR • If there is no cache entry, receiving a new RREQ an intermediate node does the following: • Starts a timer • Keeps the path cost in the header as Min-cost • Adds its own cost to the path cost in the header and broadcast • On receiving duplicate RREQ an intermediate node re-broadcasts it only if the following is true: • The timer for that RREQ has not expired • The new path cost in the header is less than Min-cost • Destination also waits for a specific time after the first RREQ arrives • It then replies to the best seen path in that period and ignores others that come later • The path cost is added to the reply and is cached by all nodes that hear the reply

PSR – Route Discovery Illustration 5 12 5 7 t2 11 @ t1 t1 3 13, 11 2 8 9 @ t3 8 S t3 D 6 reply to 11 2 4 2

PSR Route Maintenance • Node mobility Connections between some nodes on the path are lost due to their movement. In this case a new RREQ is issued and the corresponding entry in the cache is purged. • Energy Depletion Energy of some intermediate node maybe depleting very quickly. This can be addressed in two ways: • Semi-global approach Here the source monitors the remaining battery level of the path by periodically polling the intermediate nodes • Local approach Each intermediate node is allowed to send back a route error at time t if the following condition is met:

PSR Route Cache Invalidation • Once the cost of a node has increased beyond the threshold for a particular route, all cache entries to various destinations are invalidated • However if a path was newly added to the cache, the node makes some allowance by lowering the threshold by some normalized amount for forwarding packets only in that path • Invalidated routes are purged from cache after some time • A node can use an invalidated route for its own message initiations but not for relaying other node’s packets

PSR vs DSR – Simulation on NS(2) • Test bed of 20 nodes confined in 1000 x 1000 m^2 area • Range of each node is 250 m • 100 reliable and random ftp connections • Average duration of connection is 20 sec • Total simulation time 10000 sec • Speed of movement is 10 m/s • Random mobility with pause time of 4 sec

PSR vs DSR – network lifetime

PSR vs DSR – varying threshold

PSR – Points to Ponder • Threshold timers increase latency • Destination has to wait –> blocking nature • The choice of the time-out period is critical • Route invalidation based on the cost increase threshold is also a sensitive decision • Too low can force frequent route discoveries • Too high can over use a node in a path

Local Energy-Aware Routing (LEAR) • Aims to balance energy consumption with shortest routing delays • Takes into account a node’s willingness to participate in the routing path which is based on its remaining battery power • Destination does not wait to reply –> non-blocking • Efficient use of route cache

The basic LEAR Algorithm • Source uses a sequence number for new request • If it gets no reply back it increases the sequence number and re-broadcasts

LEAR – Basic Algorithm • Problems • Cannot utilize route cache in the basic form since upstream nodes cannot freely decide on behalf of downstream nodes • May incur repeated route request messages due to dropping of requests by intermediate nodes in cascade • Solutions: four additional routing control messages • DROP_ROUTE_REQ • ROUTE_CACHE • DROP_ROUTE_CACHE • CANCEL_ROUTE_CACHE

LEAR – DROP_ROUTE_REQ • The Cascading effect • Say the path is A -> B -> C1 -> C2 -> D • Each of the intermediate nodes say have low energy • On 1st request from A to D, B will drop request and adjust threshold • On 2nd request from A to D, C1 will drop and adjust, and so on • D will finally get the request on 4th attempt • DROP_ROUTE_REQ • On 1st attempt from A to D, B drops and adjusts itself and also forwards DROP_ROUTE_REQ along the path to D • This causes C1 and C2 to adjust their threshold • D will receive the request on the 2nd attempt

LEAR – ROUTE_CACHE • Destination may receive multiple ROUTE_REQ and ROUTE_CACHE • It replies to only the first one

LEAR – DROP_ROUTE_CACHE & CANCEL_ROUTE_CACHE On receiving CANCEL_ROUTE_CACHE from C1, B invalidates that entry

LEAR – Complete Algorithm

LEAR – Simulation on GloMoSim • Test bed of 40 nodes confined in 1000 x 1000 m^2 area • Range of each node is 250 m • 5 Constant Bit Rate source and destination pair chosen • 1024 byte packets sent every sec for a specified duration • Total simulation time 500 sec • Random waypoint mobility • Speed of movement is 5 m/s • Pause time is varied from 50 to 400 sec • Simulation results shown next are average of 100 runs • Initial Threshold value set to 90% of node’s initial power • The value of adjustment ‘d’ is taken as 0.1 or 0.4

LEAR – Standard Deviation of energy distribution • Energy Consumption measured at radio layer • 35% improved energy balance with high mobility (50 sec pause time) • 10% improvement with moderate mobility (400 sec pause time) • The ‘d’ value does not affect much

LEAR – Ratio of accepted ROUTE_REQ • Ratio = total route_reqs accepted / total route_reqs received • Even DSR does not have 100% ratio due to TTL • ‘d’ = 0.1 drops requests more frequently due to lower adjustment

Geographical & Energy Aware Routing (GEAR) • Mostly appropriate for static data-centric sensor networks • The basic concept comprises of two main parts: • Route packets towards a Target region through geographical and energy aware neighbor selection • Disseminate the packet within the region • The concept of the 1st part can also be applied to mobile ad-hoc networks

GEAR – Energy aware neighbor computation • Each node N maintains state h(N,R) which is called learned cost to region R • Each node infrequently updates neighbor of its cost • When a node wants to send a packet, it checks the learned cost to that region of all its neighbors • If the learned cost of a neighbor to a region is not available, the estimated cost is computed as follows: c(Ni, R) = xd(Ni, R) + (1-x)e(Ni) Where, x = tunable weight, d(Ni, R) = normalized distance of neighbor to region e(Ni) = normalized consumed energy at node i

GEAR – Packet forwarding • When a node wants to forward a packet to a destination, it checks to see if it has any neighbor closer to destination than itself • In case of multiple choices it aims to minimize the learned cost h(Ni, R) • It then sets its own cost to: h(N, R) = h(Ni, R) + C(N, Ni) Where, C(N, Ni) = combination of remaining energy of N and Ni and the distance between them

GEAR – Forwarding around holes • Incase there are no neighbors closer to destination than itself, the node forwards to the neighbor with the least learned cost • It updates its own cost accordingly • So next time it wont lie in the route to that region

GEAR – Discussions on hole avoidance • If the length of the path from S to T is n, the learned cost will converge after S delivers n packets to same target T • Convergence of learned cost only affects efficiency of hole avoidance not its correctness • Propagating learned cost further upstream through the update procedure will enable earlier chances to avoid holes

GEAR – Dissemination • Once the target region is reached the packets are disseminated within the region by recursive geographic forwarding • Forwarding stops when a node is the only one in a sub-region

GEAR – Drawback I • Inefficient Transmission • Recursive geographic forwarding vs. Restricted flooding

GEAR – Drawback II • Non-Termination • When network density is low compared to (sub) target region size

GEAR – proposed solution • Node degree is used as a criteria to differentiate low density networks from high density ones • Choice of restricted flooding over recursive geographic forwarding is made accordingly

Minimum Energy Wireless Network • What is “Minimum Energy Network”? -- It is a network where there is a path from node i to j that consumes the least transmission power . Minimum Energy Network Design --given a set of wireless nodes, for each node find a selected set of nodes called neighbors, set a directed link from the node to its neighbor (enclosure graph) --design an algorithm that will do the above function --protocol is distributed • Design first for a stationary wireless network and then extend it to a mobile scenario

Minimum Energy Network – Power Losses 1. Transmission loss which is proportional to dn where d is the distance between transmitter and receiver. n >= 2 2. Receiver power loss constant C. 3. CPU computation loss negligible. • Due to 1 above, it can be seen that relaying packets through intermediate nodes might save energy instead of directly transmitting packets.

b TD^n(bc) TD^n(ab) c a TD^n(ac) Relaying Concept • Relay through b if: tdnab+ tdnbc + C < tdnac • Relay Region: • R i->r of the transmit-relay node pair (i,r) is • R i->r = {(x,y) | P i->r->(x,y) < P i->(x,y)} • e.g, Ra->b = {c} in the above example

Power Aware Routing in Mobile Ad-Hoc Networks

Power Aware Routing in Mobile Ad-Hoc Networks

Presentation Transcript

Routing in Mobile Ad hoc Networks

Power-Aware Routing in Mobile Ad Hoc Networks

Routing in Mobile Ad-Hoc Networks

Unicast Routing in Mobile Ad-Hoc Networks

Motion-Aware Routing in Vehicular Ad-hoc Networks

Energy- Aware Routing in Mobile Ad Hoc Networks

Power-Aware Ad Hoc Routing

Routing in Mobile Ad Hoc Networks

Power-Aware Routing in Mobile Ad Hoc Networks

Signal-Strength-Aware Routing in Ad hoc Networks

Power Aware Routing in Ad Hoc Networks

Routing in Mobile Ad-hoc Networks

Routing in Mobile Ad Hoc Networks

Routing in mobile ad-hoc networks (MANETs)

Unicast Routing in Mobile Ad Hoc Networks

Routing in Mobile Ad Hoc Networks

Routing in Mobile Ad Hoc Networks

Power-Aware Ad Hoc Routing

Energy-aware routing algorithms in Ad Hoc Networks

ROUTING IN MOBILE AD-HOC NETWORKS

Power Aware Routing in Mobile Ad-Hoc Networks

Signal-Strength-Aware Routing in Ad hoc Networks