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Mobile ad hoc networking: imperatives and challenges
, 2003
"... Mobile ad hoc networks (MANETs) represent complex distributed systems that comprise wireless mobile nodes that can freely and dynamically self-organize into arbitrary and temporary, "ad-hoc" network topologies, allowing people and devices to seamlessly internetwork in areas with no pre-exi ..."
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Cited by 317 (8 self)
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Mobile ad hoc networks (MANETs) represent complex distributed systems that comprise wireless mobile nodes that can freely and dynamically self-organize into arbitrary and temporary, "ad-hoc" network topologies, allowing people and devices to seamlessly internetwork in areas with no pre-existing communication infrastructure, e.g., disaster recovery environments. Ad hoc networking concept is not a new one, having been around in various forms for over 20 years. Traditionally, tactical networks have been the only communication networking application that followed the ad hoc paradigm. Recently, the introduction of new technologies such as the Bluetooth, IEEE 802.11 and Hyperlan are helping enable eventual commercial MANET deployments outside the military domain. These recent evolutions have been generating a renewed and growing interest in the research and development of MANET. This paper attempts to provide a comprehensive overview of this dynamic field. It first explains the important role that mobile ad hoc networks play in the evolution of future wireless technologies. Then, it reviews the latest research activities in these areas, including a summary of MANET's characteristics, capabilities, applications, and design constraints. The paper concludes by presenting a set of challenges and problems requiring further research in the future.
Geometric Spanners for Wireless Ad Hoc Networks
- IEEE Transactions on Parallel and Distributed Systems
, 2003
"... We propose a new geometric spanner for static wireless ad hoc networks, which can be constructed efficiently in a localized manner. It integrates the connected dominating set and the local Delaunay graph to form a backbone of the wireless network. ..."
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Cited by 93 (25 self)
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We propose a new geometric spanner for static wireless ad hoc networks, which can be constructed efficiently in a localized manner. It integrates the connected dominating set and the local Delaunay graph to form a backbone of the wireless network.
Sift: A MAC Protocol for Event-Driven Wireless Sensor Networks
, 2003
"... Nodes in sensor networks often encounter spatially-correlated contention, where multiple nodes in the same neighborhood all sense an event they need to transmit information about. Furthermore, in many sensor network applications, it is sufficient if a subset of the nodes that observe the same even ..."
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Cited by 90 (1 self)
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Nodes in sensor networks often encounter spatially-correlated contention, where multiple nodes in the same neighborhood all sense an event they need to transmit information about. Furthermore, in many sensor network applications, it is sufficient if a subset of the nodes that observe the same event report it. We show that traditional carrier-sense multiple access (CSMA) protocols like 802.11 do not handle the first constraint adequately, and do not take advantage of the second property, leading to degraded latency and throughput as the network scales in size.
Localized construction of bounded degree and planar spanner for wireless ad hoc networks
- In DIALM-POMC
, 2003
"... We propose a novel localized algorithm that constructs a bounded degree and planar spanner for wireless ad hoc networks modeled by unit disk graph (UDG). Every node only has to know its 2-hop neighbors to find the edges in this new structure. Our method applies the Yao structure on the local Delauna ..."
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Cited by 86 (15 self)
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We propose a novel localized algorithm that constructs a bounded degree and planar spanner for wireless ad hoc networks modeled by unit disk graph (UDG). Every node only has to know its 2-hop neighbors to find the edges in this new structure. Our method applies the Yao structure on the local Delaunay graph [21] in an ordering that are computed locally. This new structure has the following attractive properties: (1) it is a planar graph; (2) its node degree is bounded from above by a positive constant 19 + ⌈ 2π α ⌉; (3) it is a t-spanner (given any two nodes u and v, there is a path connecting them in the structure such that its length is no more than t ≤ max { π α,πsin 2 2 +1}·Cdel times of the shortest path in UDG); (4) it can be constructed locally and is easy to maintain when the nodes move around; (5) moreover, we show that the total communication cost is O(n), where n is the number of wireless nodes, and the computation cost of each node is at most O(d log d), where d is its 2-hop neighbors in the original unit disk graph. Here Cdel is the spanning ratio of the Delaunay triangulation, which is at most 4 √ 3 9 π. And the adjustable parameter α satisfies 0 <α<π/3. In addition, experiments are conducted to show this topology is efficient in practice, compared with other well-known topologies used in wireless ad hoc networks. Previously, only centralized method [5] of constructing bounded degree planar spanner is known, with degree bound 27 and spanning ratio t ≃ 10.02. The distributed implementation of their centralized method takes O(n 2) communications in the worst case. No localized methods were known previously for constructing bounded degree planar spanner.
Routing for Network Capacity Maximization in Energy-constrained Ad-hoc Networks
, 2003
"... We present a new algorithm for routing of messages in ad-hoc networks where the nodes are energy-constrained. The routing objective is to maximize the total number of messages that can be successfully sent over the network without knowing any information regarding future message arrivals or message ..."
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Cited by 82 (0 self)
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We present a new algorithm for routing of messages in ad-hoc networks where the nodes are energy-constrained. The routing objective is to maximize the total number of messages that can be successfully sent over the network without knowing any information regarding future message arrivals or message generation rates. From a theoretical perspective, we show that if admission control of messages is permitted, then the worst-case performance of our algorithm is within a factor of O(log(network size)) of the best achievable solution. In other words, our algorithm achieves a logarithmic competitive ratio. Our approach provides sound theoretical backing for several observations that have been made by previous researchers. From a practical perspective, we show by extensive simulations that the performance of the algorithm is very good even in the absence of admission control (the admission control being necessary only to prove the competitive ratio result), and that it also performs better than previously proposed algorithms for other suggested metrics such as network lifetime maximization. Our algorithm uses a single shortest path computation, and is amenable to efficient implementation. We also evaluate by simulations the performance impact of inexact knowledge of residual battery energy, and the impact of energy drain due to dissemination of residual energy information.
Power Efficient and Sparse Spanner for Wireless Ad Hoc Networks
, 2001
"... Due to the limited resources available in the wireless ad hoc networking nodes, the scalability is crucial for network operations. One effective approach is to maintain only a sparse spanner of a linear number of links while still preseving the power-efficient route for any pair of nodes. For any sp ..."
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Cited by 82 (29 self)
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Due to the limited resources available in the wireless ad hoc networking nodes, the scalability is crucial for network operations. One effective approach is to maintain only a sparse spanner of a linear number of links while still preseving the power-efficient route for any pair of nodes. For any spanner #, its power stretch factor is defined as the maximum ratio of the minimum power needed to support any link in this spanner to the least necessary. In this paper, we first consider several wellknown proximity graphs including relative neighborhood graph, Gabriel graph and Yao graph. These graphs are sparse and can be constructed locally in an efficient way. We show that the power stretch factor of Gabriel graph is always one, and the power stretch factor of Yao graph is bounded by a constant while the power stretch factor of relative neighborhood graph could be as large as the network size minus one. Notice that all of these graphs do not have constant degrees. We further propose another sparse spanner that has both constant degree and constant power stretch factor. An efficient local algorithm is presented for the construction of this spanner. Keywords--- Wireless ad hoc networks, topology control, power consumption, network optimization. I.
A Case for Variable-Range Transmission Power
- Control in Wireless Multihop Networks,” Proc. IEEE INFOCOM
, 2004
"... Abstract—In this paper, we investigate the impact of variable-range transmission power control on the physical and network connectivity, on network capacity, and on power savings in wireless multihop networks. First, using previous work by Steele [18], we show that, for a path attenuation factor 2, ..."
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Cited by 81 (5 self)
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Abstract—In this paper, we investigate the impact of variable-range transmission power control on the physical and network connectivity, on network capacity, and on power savings in wireless multihop networks. First, using previous work by Steele [18], we show that, for a path attenuation factor 2, the average range of links in a planar random network of Am2 having n nodes is c ffiffiffi p A n 1. We show that this average range is approximately half the range obtained when common-range transmission control is used. Combining this result and previous work by Gupta and Kumar [8], we derive an expression for the average traffic carrying capacity of variable-range-based multihop networks. For 2, we show that this capacity remains constant even when more nodes are added to the network. Second, we derive a model that approximates the signaling overhead of a routing protocol as a function of the transmission range and node mobility for both route discovery and route maintenance. We show that there is an optimum setting for the transmission range, not necessarily the minimum, which maximizes the capacity available to nodes in the presence of node mobility. The results presented in this paper highlight the need to design future MAC and routing protocols for wireless ad hoc and sensor networks based, not on common-range which is prevalent today, but on variable-range power control. Index Terms—Multihop networks, ad hoc networks, traffic capacity, network connectivity, power savings. Ç 1
Efficient gathering of correlated data in sensor networks
- In ACM Trans. on Sensor Networks
, 2008
"... In this paper, we design techniques that exploit data cor-relations in sensor data to minimize communication costs (and hence, energy costs) incurred during data gathering in a sensor network. Our proposed approach is to select a small subset of sensor nodes that may be sufficient to re-construct da ..."
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Cited by 69 (0 self)
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In this paper, we design techniques that exploit data cor-relations in sensor data to minimize communication costs (and hence, energy costs) incurred during data gathering in a sensor network. Our proposed approach is to select a small subset of sensor nodes that may be sufficient to re-construct data for the entire sensor network. Then, during data gathering only the selected sensors need to be involved in communication. The selected set of sensors must also be connected, since they need to relay data to the data-gathering node. We define the problem of selecting such a set of sensors as the connected correlation-dominating set problem, and formulate it in terms of an appropriately de-fined correlation structure that captures general data corre-lations in a sensor network. We develop a set of energy-efficient distributed algorithms and competitive centralized heuristics to select a connected correlation-dominating set of small size. The designed dis-tributed algorithms can be implemented in an asynchronous communication model, and can tolerate message losses. We also design an exponential (but non-exhaustive) centralized approximation algorithm that returns a solution within O(log n) of the optimal size. Based on the approximation algorithm, we design a class of efficient centralized heuris-tics that are empirically shown to return near-optimal so-lutions. Simulation results over randomly generated sensor networks with both artificially and naturally generated data sets demonstrate the efficiency of the designed algorithms and the viability of our technique – even in dynamic condi-tions.
Localized Topology Control for Heterogeneous Wireless Ad-hoc Networks
, 2004
"... We study topology control in heterogeneous wireless ad hoc networks, where mobile hosts may have different maximum transmission powers and two nodes are connected iff they are within the maximum transmission range of each other. We present several strategies that all wireless nodes self-maintain sp ..."
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Cited by 67 (10 self)
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We study topology control in heterogeneous wireless ad hoc networks, where mobile hosts may have different maximum transmission powers and two nodes are connected iff they are within the maximum transmission range of each other. We present several strategies that all wireless nodes self-maintain sparse and power efficient topologies in heterogeneous network environment with low communication cost. The first structure is sparse and can be used for broadcasting. While the second structure keeps the minimum power consumption path, and the third structure is a length and power spanner with a bounded degree. Both the second and third structures are power efficient and can be used for unicast. Here a structure is power efficient if the total power consumption of the least cost path connecting any two nodes in it is no more than a small constant factor of that in the original heterogeneous communication graph. All our methods use at most O(n) total messages, where each message has O(log n) bits.
