Ad hoc and Sensor Networks Chapter 11: Routing Protocols Holger Karl
Goals of this Chapter In any network of diameter > 1, the routing & forwarding problem appears We will discuss mechanisms for constructing routing tables in ad hoc/sensor networks Specifically, when nodes are mobile Specifically, for broadcast/multicast requirements Specifically, with energy efficiency as an optimization metric Specifically, when node position is available
Overview Unicast routing in MANETs Gossiping and agent-based unicast forwarding Energy efficiency & unicast routing Multi-/broadcast routing Geographical routing Mobile nodes 3
Unicast, Id-centric Routing Given: a network/a graph Each node has a unique identifier (ID) Goal: Derive a mechanism that allows a packet sent from an arbitrary node to arrive at some arbitrary destination node The routing & forwarding problem Routing: Construct data structures (e.g., tables) that contain information how a given destination can be reached Forwarding: Consult these data structures to forward a given packet to its next hop 4
Unicast, Id-centric Routing Challenges Nodes may move around, neighborhood relations change Optimization metrics may be more complicated 5
Routing Protocols Because of challenges, standard routing approaches not really applicable Too big an overhead, too slow in reacting to changes Examples: Dijkstra s link state algorithm; Bellman-Ford distance vector algorithm 6
Routing Protocols Simple solution: Flooding Does not need any information (routing tables) simple Packets are usually delivered to destination But: overhead is prohibitive! Usually not acceptable, either! Need specific, ad hoc routing protocols
Routing Protocols Classification Main question to ask: When does the routing protocol operate? Option 1: Routing protocol always tries to keep its routing data up-to-date Protocol is proactive (routing tables are actually needed) or tabledriven Option : Route is only determined when actually needed Protocol operates on demand (reactive) Option 3: Combine these behaviors Hybrid protocols 8
Identification of Nodes Which data is used to identify nodes? An arbitrary identifier? The position of a node? Can be used to assist in geographic routing protocols because choice of next hop neighbor can be computed based on destination address Identifiers that are not arbitrary, but carry some structure? As in traditional routing Structure akin to position, on a logical level?
Overview Unicast routing in MANETs Gossiping and agent-based unicast forwarding Energy efficiency & unicast routing Multi-/broadcast routing Geographical routing Mobile nodes 10
Gossiping and Agent-based Unicast Forwarding Basic idea : Attempt to work without routing table Find a forwarding set without recurring to topology control mechanism
Gossiping and Agent-based Unicast Forwarding Basic idea : Rumor mongering Once a site receives an update, It periodically, randomly chooses another site to propagate this update to it It stop doing so after the update has already been received by a sufficient number of sites Wireless multicast advantage A single transmission can be received by all neighboring nodes in radio ranges
Randomized Forwarding How information spreads in a wireless network by such a gossiping mechanism? The key parameter of their mechanism is the probability with which a node retransmits a newly incoming message 13
Randomized Forwarding The probability with which a node retransmits a newly incoming message In the simplest case, this probability is constant. If the critical probability value below the threshold the gossip dies out quickly and reaches only a small number of nodes If the probability larger than the critical The most of gossips reach (almost) all of the nodes in the network Typical value for the critical threshold are about 65 to 75 % 14
Randomized Forwarding The node near the boundary of the sensor network s deployment region is critical as they have a smaller number of neighbors than nodes in the center of the region 15
Randomized Forwarding Possible solution: A node with few neighbors retransmit with higher probability, Retransmitting messages over the first few hops with probability 1, Retransmit a message if the node does not overhear the message repeated from at least one of its neighbors
Random Walks: Basic idea: Think of a data packet as an agent that wanders through the network in search of its destination Agents are sent via unicast Instead of single agent, several of them can be injected into the network 17
Random Walks: Rumor Routing The rumor routing Only installs a few paths in the network by sending out one or several agents 18
Random Walks: Rumor Routing The middle detects an event and installs two event paths in the network Once a node tries to query an event, it also sends out one or more agents Such a search agent is forwarded through the network until it intersects with a preinstalled event path and then knows how to find an event. 19
Random Walks: Rumor Routing The node in the lower left corner sends out such a search, which happens to propagate upward until it intersects with one event path? 0
Random Walks with Known Destination Problem: lots of nodes are redundantly deployed but some of these nodes are randomly turned off and later on again Solution: Idea: use random walks to ensure that all possible paths in the network are used with equal probability, spreading the forwarding burden over all nodes To do so, only local computations should be required for each node 1
Further Reading The basic ideas of random walks are related to biologically inspired algorithms For example, based on the behavior of ants or other swarm insects The idea of mobile agents originally contains the idea of sending code, through the network, that is executed at each node (active networks) A multipath approach where an intermediate node makes a probabilistic decision about whether to forward a packet This probability depends on distance between sensor and destination or number of hops that a packet has already traveled
Overview Unicast routing in MANETs Gossiping and agent-based unicast forwarding Energy efficiency & unicast routing Multi-/broadcast routing Geographical routing Mobile nodes 3
Energy-Efficient Unicast Particularly interesting performance metric Goals: 3 A 1 4 Minimize energy/bit Example: A-B-E-H Maximize network lifetime Time until first node failure, loss of coverage, partitioning D 3 3 B 1 E 1 H 4 G C 1 F 4 4 Example: Send data from node A to node H
Basic Options for Path Metrics Maximum total available battery capacity Path metric: Sum of battery levels Example: A-C-F-H D 3 3 A 1 B 1 4 C 1 5 3 E H 1 4 G F 4
Basic Options for Path Metrics Minimum battery cost routing (MBCR) Path metric: Sum of reciprocal battery levels Example: A-D-H D 3 3 A 1 B 1 4 C 1 6 3 E H 1 4 G F 4
Basic Options for Path Metrics Min Max Battery Cost Routing (MMBCR) Instead of using the sum of reciprocal battery levels, simply the largest reciprocal level of all nodes along a path is used as the cost for this path Then, again the path with the smallest cost is used In this sense, the optimal path is chosen by minimizing over a maximum Example: A-D-H (1/3) 3 ACFG(1/1) 7 3 D 3 A 1 B 1 E 1 H 4 4 C 1 F G 4
Basic Options for Path Metrics Conditional max-min battery capacity routing If there are routes along which all nodes have a battery level exceeding a given threshold Then select the route that requires the lowest energy per bit. If there is no such route, then pick that route which maximizes the minimum battery level 8 D 3 3 3 A 1 B 1 E H 1 4 4 G C 1 F 4
Basic Options for Path Metrics Minimize variance in power levels To avoid some nodes prematurely running out of energy and disrupting the network Hence, routes should be chosen such that the variance in battery levels between different routes is reduced D 3 3 A 1 B 1 4 C 1 9 3 E 1 H 4 G F 4
Basic Options for Path Metrics Minimum Total Transmission Power Routing (MTPR) Goal: guarantee that transmissions are successful A given transmission is successful if its SINR exceeds a given threshold MTPR is of course also applicable to multi-hop networks D 3 3 A 1 B 1 4 C 1 30 3 E 1 H 4 G F 4
Some Example Unicast Protocols Attracting routes by redirecting Idea: nodes can overhear packet exchanges between other nodes Process: Energy requirement is included in the packet When communication between two adjacent nodes X and Z proceeds, a third node Y can decide whether it can offer a more energy-efficient route. Y 1 1 3 Z 31 X
Some Example Unicast Protocols Distance vector routing on top of topology control The relay regions concept described in Section 10..3 also lends itself to a formulation of an energy-efficient routing problem 3
Some Example Unicast Protocols Maximizing time to first node outage (run out of energy) as a flow problem (normal maximum flow algorithm are not applicable ) 33
Some Example Unicast Protocols Two approximation algorithms first algorithm: find a generalized description of the costs of a link (consider energy cost, initial and residual battery capacity.) second algorithm is a flow redirection algorithm The core result is that system lifetime can be extended up to 60% 34 D 3 3 3 A 1 B 1 E 1 H 4 4 G C 1 F 4
Some Example Unicast Protocols Maximizing time to first node outage by a max min optimization There are two algorithms The max min zpmin approximation: the minimal remaining power in all nodes is the largest. Property: Require knowledge of battery power level May pick a very expensive path Sol: Pick a path having at most a power consumption of zpmin The zone routing approximation can work without this information at only slightly reduced performance 35
Some Example Unicast Protocols Maximizing number of messages The goal is to maximize the number of messages that can be sent over a network before it runs out of energy 36
Some Example Unicast Protocols One non-trivial link weight: w ij weight for link node i to node j e ij required energy, λ some constant, α i fraction of battery of node i already used up Path metric: Sum of link weights Use path with smallest metric Properties: Many messages can be send, high network lifetime 37
Some Example Unicast Protocols Bounding the difference between routing protocols the graph is partitioned into spheres Si that include all the nodes that are reachable from the base station in at most i hops 38
Some Example Unicast Protocols Bounding the difference between routing protocols Then, all traffic has to go through the nodes of sphere S1, and because there are relatively few of these nodes, they limit the lifetime of the network 39
Multipath Unicast Routing Multiple paths between a given source/destination pair Energy consumption across multiple path is therefore an option worthwhile exploring Fault-tolerance: multiple paths provide redundancy in that they can serve as hot standbys to quickly switch to when a node or a link on a primary path fails 40
Multipath Unicast Routing Sequential Assignment Routing (SAR) Problem : computing such k-disjoint paths requires about k times more overhead than a single-path routing protocol SAR : require paths different neighbors of the sink. constructing trees outward from each sink neighbor; in the end, most nodes will then be part of several such trees 41
Multipath Unicast Routing Constructing energy-efficient secondary paths Concern: the energy efficiency of these secondary paths compared to the optimal primary path 4
Multipath Unicast Routing For disjoint paths, Primary path: via its best neighbor toward the data source neighbor This alternate path: forwarded toward the best neighbor that is not already on the primary path. 43
Multipath Unicast Routing For braided paths, Require to leave out some nodes of the primary path but are free to use other nodes on the primary path. 44
Multipath Unicast Routing Simultaneous transmissions over multiple paths There is some delay in detecting the need to use a secondary path The idea assume node-disjoint paths send several copies of a given packet over these different paths to the destination This trades off resource consumption against packet error rates 45
Multipath Unicast Routing Randomly choosing one of several paths Each node maintains an energy cost estimate for each of its neighbors The next hop is randomly chosen proportional to the energy consumption of the path over this neighbor 46
Multipath Unicast Routing Randomly choosing one of several paths Suppose node v has neighbors v1 to vn that advertise cost c1,..., cn, respectively Node v will advertise as its own cost Node v forward an incoming packet to neighbor i with probability 47
Multipath Unicast Routing Trade-off analysis Supporting such multiple paths in a network implies a trade-off between robustness and energy efficiency This tradeoff is analyzed by Krishnamachari et al. [440], who compare the robustness gained by multiple paths with those owing to simply increasing transmission power Result: Single path with a larger transmission power dominates. 48
Overview Unicast routing in MANETs Gossiping and agent-based unicast forwarding Energy efficiency & unicast routing Multi-/broadcast routing Geographical routing Mobile nodes 49
Broadcast & Multicast(Energy-Efficient) Distribute a packet to all reachable nodes (broadcast) or to a somehow (explicitly) denoted subgroup (multicast) 50
Broadcast & Multicast(Energy-Efficient) Basic options Source-based tree: Construct a tree (one for each source) to reach all addressees Minimize total cost (= sum of link weights) of the tree Minimize maximum cost to each destination Shared, core-based trees Use only a single tree for all sources Every source sends packets to the tree where they are distributed Mesh Trees are only 1-connected! Provide higher redundancy and thus robustness in mobile environments 51
Broadcast & Multicast (Energy-Efficient) Source-based tree: For each source, minimize the total cost Try to find a tree for which the sum of all link costs is minimal (over all possible trees rooted at the source) This is the Steiner tree problem 5
Broadcast & Multicast (Energy-Efficient) Source-based tree: For each source, minimize the maximum cost to each destination minimize the costs to each individual destination separately In effect, this maps the multicast problem to repeated unicast shortest path problems, 53
Broadcast & Multicast (Energy-Efficient) Shared, core-based trees Use only a single tree for all sources Every source sends packets to the tree where they are distributed 54
Broadcast & Multicast (Energy-Efficient) Mesh Trees are only 1-connected! use meshes to provide higher redundancy and thus robustness in mobile environments 55
Summary of Options (Broadcast/Multicast) Broadcast Multicast One tree per source Shared tree (core-based tree) Mesh Minimize total cost (Steiner tree) Minimize cost to each node (e.g., Dijkstra) Single core Multiple core 56
Wireless Multicast Advantage Broad-/Multicasting in wireless is unlike broad- /multicasting in a wired medium Wires: Locally distributing a packet to n neighbors: n times the cost of a unicast packet Wireless: sending to n neighbors can incur costs As high as sending to a single neighbor if receive costs are neglected completely As high as sending once, receiving n times if receives are tuned to the right moment As high as sending n unicast packets if the MAC protocol does not support local multicast 57
Source-Based Tree Protocols A greedy heuristic Shortest Path Tree the shortest path and overlay all these paths onto a tree Shortest Path Tree (SPT) this greedy heuristic does not have a good approximation ratio 58
Source-Based Tree Protocols Broadcasting using minimum cost spanning tree Prim s algorithm A simple broadcasting algorithm can be based on a minimum cost spanning tree. One possible algorithm to compute it is due to Prim 59
Source-Based Tree Protocols Some Steiner tree approximations for multicasting Computing Steiner tree is NP complete A simple approximation Pick some arbitrary order of all destination nodes + source node Successively add these nodes to the tree: For every next node, construct a shortest path to some other node already on the tree Performs reasonably well in practice 60
Source-Based Tree Protocols Some Steiner tree approximations for multicasting Takahashi Matsuyama heuristic Similar, but let algorithm decide which is the next node to be added Start with source node, add that destination node to the tree which has shortest path Iterate, picking that destination node which has the shortest path to some node already on the tree 61
Exploiting Wireless Multicast Advantage for Broadcast Broadcast incremental power The core idea is that a node that is already transmitting to some other node would only have to raise its transmission power in order provide data also to further nodes, without incurring cost for another transmission the additional cost for a node to supply a further node with data is only the difference between the current and the needed (higher) transmission power On the basis of this idea, a modification of Prim s algorithm is possible 6
BIP Example Round 1: A Round : A Round 3: A 5 3 4 3 3 S 1 B S (1) B S (3) B 10 3 7 9 7 7 7 D 1 C Round 4: A D 1 C Round 5: A D 1 C S (3) 3 B S (5) 3 B 7 6 10 7 63 D C (1) D C (1)
Sweep Operation 64
Exploiting Wireless Multicast Advantage for Multicast Pruning broadcast trees by Multicast Incremental Power (MIP) Given a broadcast tree, Prune it by removing all nodes from the tree that have no members of the destination set as downstream nodes In addition, the sweep operation can be applied to reduce transmission power if high power is only needed to supply subtrees without any destination nodes. 65
Embedded Wireless Multicast Advantage Transforming Existing Graphs A different approach to leverage the wireless multicast advantage Start from a traditional, link-oriented broadcast tree, ex: the minimum-cost spanning tree Look for opportunities to increase transmission power levels of certain trees such that the additionally covered nodes can stop transmitting and the resulting, 66
A Distributed, Position-Based Approach to the Wireless Multicast Mdvantage Start from Relative Neighborhood Graph (RNG) u and v are connected if no w that is close to each of u and v For each v, the transmission range as the smallest range that connect v and its neighbors. Take the wireless multicast advantage The RNG-based scheme is advantageous, especially in dense networks 67
Shared, Core-based Tree Protocols The challenge in core-based tree multicast protocols lies in finding a good core node. Once this node is determined, essentially the problem can be reformulated as a source-based tree protocol with the core node as the source 68
Shared, Core-based Tree Protocols Merge point formation Assume there are a few sinks in a network to which data shall be distributed via a core-based multicast tree Process Each sink broadcast advertisement messages indicating its presence. Each node collect these advertisement along with sink ID and number of hops After a certain time, each node that has received more than one sink advertisement broadcasts merge advertisement messages. These messages are only forwarded by nodes that have heard from fewer sinks or whose cumulative distance to all sinks is larger 69
Mesh-Based Protocols Core-Assisted Mesh Protocol (CAMP) The redundancy of the mesh can actually enable shorter paths in the mesh than would be possible in a core-based tree However, up to the forwarding procedure to actually be able to exploit these shortcuts without resorting to flooding the entire mesh with data. 70
Mesh-Based Protocols Two-tier data dissemination Overlay a mesh, route along mesh intersections Broadcast within the quadrant where the destination is (assumed to be) located Sink Event 71
Further reading on broadcast and multicast Gossiping for multicast Gossiping is used to improve the reliability of multicasting Directed antennas for multicasting Assuming that directed antennas can be used to concentrate power to the neighbors in the multicast tree and thus reduce power consumption. Optimal solutions by linear programming This modeling approach obviously does not change the complexity of the problem (integer linear programming is NPhard), it can often lead to good approximations of the optimal solutions by standard relaxation techniques 7
Further reading on broadcast and multicast Time to complete a multicast Mostly the energy required for a multicast or broadcast has been considered. But the time necessary to do so can also be important Data placement There is a further variant of Steiner tree approximations which boils down to choosing good Steiner points. Cooperative multihop broadcast Using advanced signal processing, a node might be able to reconstruct the correct packet even if each individual reception is erroneous 73
Overview Unicast routing in MANETs Gossiping and agent-based unicast forwarding Energy efficiency & unicast routing Multi-/broadcast routing Geographical routing Position-based routing Geocasting Mobile nodes 74
Geographic routing Routing tables contain information to which next hop a packet should be forwarded Explicitly constructed Alternative: Implicitly infer this information from physical placement of nodes Position of current node, current neighbors, destination known send to a neighbor in the right direction as next hop Geographic routing 75
Geographic routing Options Send to any node in a given area geocasting Use position information to aid in routing position-based routing Might need a location service to map node ID to node position 76
Basics of position-based routing Most forward within range r strategy Send to that neighbor that realizes the most forward progress towards destination Note: farthest away from sender! 77
Basics of position-based routing Nearest node with (any) forward progress Idea: Minimize transmission power Directional routing Choose next hop that is angularly closest to destination Choose next hop that is closest to the connecting line to destination Problem: Might result in loops! 78
Basics of position-based routing The problem of dead ends Simple strategies might send a packet into a dead end 79
Basics of position-based routing Restricted flooding Restricted flooding is quite suited to compensate for mobility of the destination. Assume that the destination moves at a given speed v the distance between transmitting node and destination is known, a source forwards to some of or all of the nodes that are closer to the destination than itself 80
Right hand rule to leave dead ends GPSR Basic idea to get out of a dead end: Put right hand to the wall, follow the wall Does not work if on some inner wall will walk in circles Need some additional rules to detect such circles 81
Right hand rule to leave dead ends GPSR Geometric Perimeter State Routing (GPSR) Earlier versions: Compass Routing II, face- routing Use greedy, most forward routing as long as possible If no progress possible: Switch to face routing Face: largest possible region of the plane that is not cut by any edge of the graph; can be exterior or interior Send packet around the face using right-hand rule Use position where face was entered and destination position to determine when face can be left again, switch back to greedy routing Requires: planar graph! (topology control can ensure that) 8
GPSR Example Route packet from node A to node Z Leave face routing E I B F H K A D Z Enter face routing C G J L 83
Performance guarantees of combined greedy/face routing Face routing is tasked with routing around obstacles or out of dead ends while greedy routing tries to make quick progress toward the destination The first combined greedy/face routing algorithm that is provably worst-case optimal In order to show the worst-case optimality, quickly switching back to greedy routing could not be used the Greedy and (Other Adaptive) Face Routing (GOAFR)+ algorithm that is worst-case optimal and at the same time efficient in the average case 84
GOAFR+ algorithm The algorithm maintains a bounding circle, centered at the destination node, that prevents the face search from needlessly exploring in the wrong direction A packet maintains two counters, p and q Counter p contains the number of nodes on the face perimeter that are closer to the destination than is the node where face search started; Counter q counts nodes farther away 85
Combination with ID-base routing Pure position-baseed routing in Mobile destination node, immediate vicinity can be problematic Solution: by ID
GeRaF How to combine position knowledge with nodes turning on/off? Goal: Transmit message over multiple hops to destination node; deal with topology constantly changing because of on/off node Idea: Receiver-initiated forwarding Forwarding node S simply broadcasts a packet, without specifying next hop node Some node T will pick it up (ideally, closest to the source) and forward it 87
GeRaF Problem: How to deal with multiple forwarders? Position-informed randomization: The closer to the destination a forwarding node is, the shorter does it hesitate to forward packet Use several annuli to make problem easier, group nodes according to distance (collisions can still occur) 88
GeRaF Example A 4 A 3 A A 1 89 1 D-1 D
Geographic routing without positions GEM Apparent contradiction: geographic, but no position? virtual coordinates preserve enough neighborhood information to be useful in geographic routing do not require actual position determination
Geographic routing without positions GEM Two essential parts: Use polar coordinates from a center point Assign virtual angle range to neighbors of a node, Construct a spanning tree with the center point as the root. Define the radius of a node by the number of hops (in spanning tree) 91
Geographic routing without positions GEM Process: Choose two nodes in addition to the original root. Determine, for each node, the hop count of the shortest path between each of these three nodes(so, total three spanning tree) Each node can triangulate its own position in the hop count metric. 9
Overview Unicast routing in MANETs Gossiping and agent-based unicast forwarding Energy efficiency & unicast routing Multi-/broadcast routing Geographical routing Position-based routing Geocasting Mobile node 93
Location-based Multicast (LBM) Geocasting by geographically restricted flooding Define a forwarding zone nodes in this zone will forward the packet to make it reach the destination zone 94
Location-based Multicast (LBM) Static zone: smallest rectangle that contains both the source and the entire destination region. Adaptive zone smallest rectangle containing forwarding node and destination zone Possible dead ends again Adaptive distances packet is forwarded by node u if node u is closer to destination zone s center than predecessor node v (packet has made progress) Packet is always forwarded by nodes within the destination zone itself otherwise. 95
Determining next hops based on Voronoi diagrams Goal: Use that neighbor to forward packet that is closest to destination among all the neighbors Use Voronoi diagram computed for the set of neighbors of the node currently holding the packet B C A S D 96
Tessellating the plane Tessellation: of the plane is a collection of plane figures that fills the plane with no overlaps and no gaps The first protocol uses a fixed tessellation of the plane into hexagons where each hexagon either has a manager in charge of it or is classified as an obstacle to be rooted around 97
Tessellating the plane The second protocol is GeoGRID The plane is divided into square grids where each grid has an elected gateway in charge of it. Only those gateway nodes propagate packets among different grids, resulting in a need to control the size of such a grid 98
Mesh-based geocasting Geocast Adaptive Mesh Environment for Routing (GAMER) a mesh-based protocol for geocasting It improves upon other mesh-based geocasting protocols by adapting the density of the created mesh according to the mobility of the nodes in the network 99
Geocasting using ad hoc routing GeoTORA GeoTORA: All nodes in the destination region act as sinks Different nodes have different heights above ground. Destination is the lowest point No local minimum. 100
Trajectory-based forwarding (TBF) Think in terms of an agent : Should travel around the network, e.g., collecting measurements Random forwarding may take a long time Idea: Provide the agent with a certain trajectory along which to travel Described, e.g., by a simple curve Forward to node closest to this trajectory 101
Further reading on geographic routing Impact of localization errors In a real system, it is unrealistic to expect that all nodes know their correct positions Location services This service is important for ad hoc or Internet-based geographic information but rarely needed in WSNs Such position databases or location tables can be organized centrally or the information can be kept distributed in structures akin to routing tables 10
Further reading on geographic routing Location-Aided Routing (LAR) This protocol uses location information to assist in the flooding phases of standard ad hoc routing protocols The protocol is similar in many respects to the LBM Making geocasting energy aware Geographic and Energy Aware Routing (GEAR) is a geocasting scheme that introduces load-splitting among neighbors when forwarding toward the target region, trying to equalize the energy consumption of all nodes 103
Further reading on geographic routing Geographic routing without geographic coordinates The coordinates used for geographic routing are purely virtual ones and are constructed without actually recurring to the physical location of nodes at all Another schemes where perimeter nodes do not know their location and show that, even then, virtual coordinates are still useful for geographic routing protocols 104
Overview Unicast routing in MANETs Energy efficiency & unicast routing Multi-/broadcast routing Geographical routing Mobile nodes 105
Mobile nodes, mobile sinks Mobile nodes cause some additional problems E.g., multicast tree to distribute readings has to be adapted Source Sink moves downward Source Source Sink moves upward 106
Mobile data collectors Sometimes, it is not possible or desirable to move the actual data sinks around but using multihop communication might also not be useful Mobile Ubiquitous LAN extensions (MULEs) MULE is a mobile device, equipped with radio front ends to communicate with sensor nodes, that moves around between the sensor nodes, collects and buffers their data, and occasionally visits the actual data sink to off-load that data. MULEs are considerably more energy efficient than multihop communication and can increase lifetime of the network without impeding data collection quality too much 107
Mobile regions The geocast destination regions so far considered were static For some applications like tracking mobile events, it would be useful to be able to specify a destination zone that changes its location over time. For such a moving zone, data should be delivered at time t to all nodes that are covered by the destination zone at time t. This service model is called mobicast 108
Conclusion Routing exploit various sources of information to find destination of a packet Explicitly constructed routing tables Implicit topology/neighborhood information via positions Routing can make some difference for network lifetime However, in some scenarios (streaming data to a single sink), there is only so much that can be done Energy efficiency does not equal lifetime, holds for routing as well Non-standard routing tasks (multicasting, geocasting) require adapted protocols 109