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24
GPSR: Greedy perimeter stateless routing for wireless networks
, 2000
"... karp @ eecs.harvard.edu We present Greedy Perimeter Stateless Routing (GPSR), a novel routing protocol for wireless datagram networks that uses the positions of touters and a packer's destination to make packet forwarding decisions. GPSR makes greedy forwarding decisions using only informati ..."
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Cited by 2143 (9 self)
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karp @ eecs.harvard.edu We present Greedy Perimeter Stateless Routing (GPSR), a novel routing protocol for wireless datagram networks that uses the positions of touters and a packer's destination to make packet forwarding decisions. GPSR makes greedy forwarding decisions using only information about a router's immediate neighbors in the network topology. When a packet reaches a region where greedy forwarding is impossible, the algorithm recovers by routing around the perimeter of the region. By keeping state only about the local topology, GPSR scales better in perrouter state than shortestpath and adhoc routing protocols as the number of network destinations increases. Under mobility's frequent topology changes, GPSR can use local topology information to find correct new routes quickly. We describe the GPSR protocol, and use extensive simulation of mobile wireless networks to compare its performance with that of Dynamic Source Routing. Our simulations demonstrate GPSR's scalability on densely deployed wireless networks.
Distributed topology control for power efficient operation in multihop wireless ad hoc networks
, 2001
"... Abstract — The topology of wireless multihop ad hoc networks can be controlled by varying the transmission power of each node. We propose a simple distributed algorithm where each node makes local decisions about its transmission power and these local decisions collectively guarantee global connecti ..."
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Cited by 363 (19 self)
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Abstract — The topology of wireless multihop ad hoc networks can be controlled by varying the transmission power of each node. We propose a simple distributed algorithm where each node makes local decisions about its transmission power and these local decisions collectively guarantee global connectivity. Specifically, based on the directional information, a node grows it transmission power until it finds a neighbor node in every direction. The resulting network topology increases network lifetime by reducing transmission power and reduces traffic interference by having low node degrees. Moreover, we show that the routes in the multihop network are efficient in power consumption. We give an approximation scheme in which the power consumption of each route can be made arbitrarily close to the optimal by carefully choosing the parameters. Simulation results demonstrate significant performance improvements. I.
Gossipbased ad hoc routing
, 2002
"... Abstract—Many ad hoc routing protocols are based on some variant of flooding. Despite various optimizations, many routing messa ges are propagated unnecessarily. We propose a gossipingbased approa ch, where each node forwards a message with some probability, to reduce the ov erhead of the routing p ..."
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Cited by 359 (4 self)
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Abstract—Many ad hoc routing protocols are based on some variant of flooding. Despite various optimizations, many routing messa ges are propagated unnecessarily. We propose a gossipingbased approa ch, where each node forwards a message with some probability, to reduce the ov erhead of the routing protocols. Gossiping exhibits bimodal behavio r in sufficiently large networks: in some executions, the gossip dies out quic kly and hardly any node gets the message; in the remaining executions, a sub stantial fraction of the nodes gets the message. The fraction of execution s in which most nodes get the message depends on the gossiping probability a nd the topology of the network. In the networks we have considered, using g ossiping probability between 0.6 and 0.8 suffices to ensure that almost every node gets the message in almost every execution. For large networ ks, this simple gossiping protocol uses up to 35 % fewer messages than flood ing, with improved performance. Gossiping can also be combined with va rious optimizations of flooding to yield further benefits. Simulations show that adding gossiping to AODV results in significant performance improv ement, even in networks as small as 150 nodes. We expect that the improvemen t should be even more significant in larger networks. I.
Minimum energy mobile wireless networks revisited
 In IEEE International Conference on Communications (ICC
, 2001
"... Energy conservation is a critical issue in designing wireless ad hoc networks, as the nodes are powered by batteries only. Given a set of wireless network nodes, the directed weighted transmission graph Gt has an edge uv if and only if node v is in the transmission range of node u and the weight of ..."
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Cited by 162 (9 self)
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Energy conservation is a critical issue in designing wireless ad hoc networks, as the nodes are powered by batteries only. Given a set of wireless network nodes, the directed weighted transmission graph Gt has an edge uv if and only if node v is in the transmission range of node u and the weight of uv is typically defined as II,,vll + c for a constant 2 <_ t ~ < 5 and c> O. The minimum power topology Gm is the smallest subgraph of Gt that contains the shortest paths between all pairs of nodes, i.e., the union of all shortest paths. In this paper, we described a distributed positionbased networking protocol to construct an enclosure graph G~, which is an approximation of Gin. The time complexity of each node u is O(min(dG ~ (u)dG ~ (u), dG ~ (u) log dG ~ (u))), where dc(u) is the degree of node u in a graph G. The space required at each node to compute the minimum power topology is O(dG ~ (u)). This improves the previous result that computes Gm in O(dG, (u) a) time using O(dGt(U) 2) spaces. We also show that the average degree dG,(u) is usually a constant, which is at most 6. Our result is first developed for stationary network and then extended to mobile networks. I.
Geographic Routing for Wireless Networks
 Harvard University
, 2000
"... und the perimeter of the region. By keeping state only about the local topology, GPSR scales better in perrouter state than shortestpath and adhoc routing protocols as the number of network destinations increases. Under mobility's frequent topology changes, GPSR can use local topology inform ..."
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Cited by 104 (6 self)
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und the perimeter of the region. By keeping state only about the local topology, GPSR scales better in perrouter state than shortestpath and adhoc routing protocols as the number of network destinations increases. Under mobility's frequent topology changes, GPSR can use local topology information to find correct new routes quickly. We describe the GPSR protocol, and use extensive simulation of mobile wireless networks to compare its performance with that of Dynamic Source Routing. Our simulations demonstrate GPSR's iii scalability on densely deployed wireless networks. iv Contents 1 Introduction 1 1.1 Metrics for Evaluating Routing Scalability . . . . . . . . . . . . . . . . . . 3 1.2 Traditional ShortestPath Algorithms . . . . . . . . . . . . . . . . . . . . . 4 1.3 AdHoc Routing Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . 5 1.4 Techniques for Routing Scalability . . . . . . . . . . . . . . . . . . . . . . 7 1.5 Applica
A ConeBased Distributed TopologyControl Algorithm for Wireless MultiHop Networks
 IEEE/ACM TRANSACTIONS ON NETWORKING
, 2002
"... The topology of a wireless multihop network can be controlled by varying the transmission power at each node. In this paper, we give a detailed analysis of a conebased distributed topology control algorithm. This algorithm does not assume that nodes have GPS information available; rather it dep ..."
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Cited by 56 (1 self)
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The topology of a wireless multihop network can be controlled by varying the transmission power at each node. In this paper, we give a detailed analysis of a conebased distributed topology control algorithm. This algorithm does not assume that nodes have GPS information available; rather it depends only on directional information. Roughly speaking, the basic idea of the algorithm is that a node u transmits with the minimum power p u,# required to ensure that in every cone of degree # around u, there is some node that u can reach with power p u,# . We show that taking # = 5#/6 is a necessary and sufficient condition to guarantee that network connectivity is preserved. More precisely, if there is a path from s to t when every node communicates at maximum power then, if # 5#/6, there is still a path in the smallest symmetric graph G # containing all edges (u, v) such that u can communicate with v using power p u,# . On the other hand, if # > 5#/6,
A MinimumEnergy PathPreserving TopologyControl Algorithm
"... The topology of a wireless multihop network can be controlled by varying the transmission power at each node. In general, it is not energy efficient to use the communication network where every node transmits with maximum power. For energy efficient operations, it is desirable to have a subnetwork ..."
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Cited by 13 (1 self)
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The topology of a wireless multihop network can be controlled by varying the transmission power at each node. In general, it is not energy efficient to use the communication network where every node transmits with maximum power. For energy efficient operations, it is desirable to have a subnetwork that preserves a minimumenergy path between every pair of nodes (where a minimumenergy path is one that allows messages to be transmitted with a minimum use of energy). In this paper, we first identify conditions that are necessary and sufficient for a subnetwork of to preserve this property. Using this characterization, we then propose an efficient topologycontrol algorithm that, given a communication network, computes a subnetwork that it preserves at least one minimumenergy path between every pair of nodes. We also propose an energyefficient reconfiguration protocol that maintains this minimumenergy path property as the network topology changes dynamically. We demonstrate the performance improvements of our algorithm over other existing topologycontrol algorithms through simulation.
Clustered Mobility Model for ScaleFree Wireless Networks
"... Abstract — Recently, researchers have discovered that many of social, natural and biological networks are characterized by scalefree powerlaw connectivity distribution and a few densely populated nodes, known as hubs. We envision that wireless communication or sensor networks are directly deployed ..."
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Cited by 8 (0 self)
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Abstract — Recently, researchers have discovered that many of social, natural and biological networks are characterized by scalefree powerlaw connectivity distribution and a few densely populated nodes, known as hubs. We envision that wireless communication or sensor networks are directly deployed over such realworld networks to facilitate communication among participating entities. Here nodes move in such a way that they exhibit scalefree connectivity distribution at any instance, which cannot be modeled by most of the prior mobility models such as random waypoint (RWP) mobility model. This paper proposes clustered mobility model (CMM), which facilitates in forming hubs in a network satisfying the scalefree property. We call this a scalefree wireless network (SFWN). In CMM, it is possible to control the degree of node concentration or nonhomogeneity to easily assess the strengths and weaknesses of the scalefree phenomena. To the best of the authors ’ knowledge, there has been no such mobility model reported in the literature and we believe the proposed CMM can be usefully used to investigate the properties of the SFWNs that are likely to occur in a real deployment of wireless multihop and sensor networks. Another important feature of CMM is that it does not possess any unintended spatial and temporal characteristics found in other mobility models such as RWP. Finally, to highlight the difference between a SFWN and a conventional wireless network, extensive simulation study has been conducted to measure network capacities at the physical, link and network layers. Index Terms — Connectivity distribution, mobility model, network capacity, random waypoint mobility, scalefree wireless networks. I.
Rcast: A Randomized Communication Scheme for Improving Energy Efficiency
 in Mobile Ad Hoc Networks,” Proc. 25th IEEE Int’l Conf. Distributed Computing Systems
, 2005
"... In a typical wireless mobile ad hoc network (MANET) using a shared communication medium, every node receives or overhears every data transmission occurring in its vicinity. However, this technique is not applicable when a power saving mechanism (PSM) such as the one specified in IEEE 802.11 is emplo ..."
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Cited by 7 (0 self)
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In a typical wireless mobile ad hoc network (MANET) using a shared communication medium, every node receives or overhears every data transmission occurring in its vicinity. However, this technique is not applicable when a power saving mechanism (PSM) such as the one specified in IEEE 802.11 is employed, where a packet advertisement period is separated from the actual data transmission period. When a node receives an advertised packet that is not destined to itself, it switches to a lowpower state during the data transmission period, and thus, conserves power. However, since some MANET routing protocols such as Dynamic Source Routing (DSR) collect route information via overhearing, they would suffer if they are used with the IEEE 802.11 PSM. Allowing no overhearing may critically deteriorate the performance of the underlying routing protocol, while unconditional overhearing may offset the advantage of using PSM. This paper proposes a new communication mechanism, called RandomCast or Rcast, via which a sender can specify the desired level of overhearing in addition to the intended receiver. Therefore, it is possible that only a random set of nodes overhear and collect route information for future use. Rcast improves not only the energy efficiency, but also the energy balance among the nodes, without significantly affecting the routing efficiency. Extensive simulation using the ns2 network simulator shows that Rcast is highly energyefficient compared to the original IEEE 802.11 PSM and OnDemand Power Management (ODPM) protocol in terms of total energy consumption
Throughput and energy efficiency in topologycontrolled multihop wireless sensor networks
 Wireless Sensor Networks and Applications (WSNA
, 2003
"... In the context of multihop wireless networks, various topology control algorithms have been proposed to adapt the transmission range of nodes based on local information while maintaining a connected topology. These algorithms are particularly suited for deployment in sensor networks which typically ..."
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Cited by 6 (0 self)
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In the context of multihop wireless networks, various topology control algorithms have been proposed to adapt the transmission range of nodes based on local information while maintaining a connected topology. These algorithms are particularly suited for deployment in sensor networks which typically consist of energy constrained sensors. Sensor nodes should support power adaptation in order to use the benefits of topology control for energy conservation. In this paper, we design a framework for evaluating the performance of topology control algorithms using overall network throughput, and total energy consumption per packet delivered, as the metrics. Our goal is to identify the scenarios in which topology control improves the network performance. We supplement our analysis with ns2 simulations using the conebased topology control algorithm [10, 19]. Based on our analysis and simulations, we find that link layer retransmissions are essential with topology control to avoid throughput degradation due to increase in number of hops in lightly loaded networks. In heavily loaded networks, the throughput can be improved by a factor up to k 2,where k is the average factor of reduction in transmission range using topology control. Studies of energy consumption reveal that improvements of up to k 4 can be obtained using topology control. However, these improvements decrease as the traffic pattern shifts from local (few hop connections) to nonlocal (hop lengths of the order of the diameter of the network). These results can be used to guide the deployment of topology control algorithms in sensor networks.