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Connectivity Maintenance in Mobile Wireless Networks via Constrained Mobility
"... Abstract—We explore distributed mechanisms for maintaining the physical layer connectivity of a mobile wireless network while still permitting significant area coverage. Moreover, we require that these mechanisms maintain connectivity despite the unpredictable wireless propagation behavior found in ..."
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Abstract—We explore distributed mechanisms for maintaining the physical layer connectivity of a mobile wireless network while still permitting significant area coverage. Moreover, we require that these mechanisms maintain connectivity despite the unpredictable wireless propagation behavior found in complex realworld environments. To this end, we propose the Spreadable Connected Autonomic Network (SCAN) algorithm, a fully distributed, online, low overhead mechanism for maintaining the connectivity of a mobile wireless network. SCAN leverages knowledge of the local (2hop) network topology to enable each node to intelligently halt its own movement and thereby avoid network partitioning events. By relying on topology data instead of locality information and deterministic connectivity models, SCAN can be applied in a wide range of realistic operational environments. We believe it is for precisely this reason that, to our best knowledge, SCAN was the first such approach to be implemented in hardware. Here, we present results from our implementation of SCAN, finding that our mobile robotic testbed maintains full connectivity over 99 % of the time. Moreover, SCAN achieves this in a complex indoor environment, while still allowing testbed nodes to cover a significant area. I.
Optimal Deployment of Impromptu Wireless Sensor Networks
"... Abstract—The need for impromptu wireless networks arises in emergency situations where the team responding to the emergency, needs to deploy sensors (such as motion sensors, or even imaging sensors) and a wireless interconnection network, without any prior planning or knowledge of the terrain. In th ..."
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Abstract—The need for impromptu wireless networks arises in emergency situations where the team responding to the emergency, needs to deploy sensors (such as motion sensors, or even imaging sensors) and a wireless interconnection network, without any prior planning or knowledge of the terrain. In this paper, we consider a simple model for the sequential deployment of wireless relays as a person steps along a “corridor ” of unknown length, so as to create a multihop network for interconnecting a sensor to be placed at the end of the corridor with a control truck standing near the entry to the corridor. Assuming low traffic and simple linkbylink scheduling, we consider the problem of minimising an endtoend cost metric (e.g., delay or power from the sensor to the control centre) subject to a constraint on the number of relays. Two kinds of constraints are considered: the expected number of relays is bounded, or the actual number of relays is bounded. In each case, the problem is formulated as a Markov decision process. The problem of deciding whether or not to place a relay at each step is shown to be equivalent to a certain stochastic shortest path problem embedded at relay placement points. Numerical results are provided to illustrate the performance tradeoffs. I.
Optimal sequential wireless relay placement on a random lattice path
"... Keywords: Relay placement Asyougo deployment of wireless sensor networks Optimal stopping problems Placement boundary a b s t r a c t Our work is motivated by impromptu (or ''asyougo'') deployment of wireless relay nodes along a path, a need that arises in many situations. I ..."
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Keywords: Relay placement Asyougo deployment of wireless sensor networks Optimal stopping problems Placement boundary a b s t r a c t Our work is motivated by impromptu (or ''asyougo'') deployment of wireless relay nodes along a path, a need that arises in many situations. In this paper, the path is modeled as starting at the origin (where there is the data sink, e.g., the control center), and evolving randomly over a lattice in the positive quadrant. A person walks along the path deploying relay nodes as he goes. At each step, the path can, randomly, either continue in the same direction or take a turn, or come to an end, at which point a data source (e.g., a sensor) has to be placed, that will send packets to the data sink. A decision has to be made at each step whether or not to place a wireless relay node. Assuming that the packet generation rate by the source is very low, and simple linkbylink scheduling, we consider the problem of sequential relay placement so as to minimize the expectation of an endtoend cost metric (a linear combination of the sum of convex hop costs and the number of relays placed). This impromptu relay placement problem is formulated as a total cost Markov decision process. First, we derive the optimal policy in terms of an optimal placement set and show that this set is characterized by a boundary (with respect to the position of the last placed relay) beyond which it is optimal to place the next relay. Next, based on a simpler onesteplookahead characterization of the optimal policy, we propose an algorithm which is proved to converge to the optimal placement set in a finite number of steps and which is faster than value iteration. We show by simulations that the distance threshold based heuristic, usually assumed in the literature, is close to the optimal, provided that the threshold distance is carefully chosen.
Optimal Sequential Wireless Relay Placement on a Random Lattice Path
"... Our work is motivated by impromptu (or “asyougo”) deployment of wireless relay nodes along a path, a need that arises in many situations. In this paper, the path is modeled as starting at the origin (where there is the data sink, e.g., the control centre), and evolving randomly over a lattice in t ..."
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Our work is motivated by impromptu (or “asyougo”) deployment of wireless relay nodes along a path, a need that arises in many situations. In this paper, the path is modeled as starting at the origin (where there is the data sink, e.g., the control centre), and evolving randomly over a lattice in the positive quadrant. A person walks along the path deploying relay nodes as he goes. At each step, the path can, randomly, either continue in the same direction or take a turn, or come to an end, at which point a data source (e.g., a sensor) has to be placed, that will send packets to the data sink. A decision has to be made at each step whether or not to place a wireless relay node. Assuming that the packet generation rate by the source is very low, and simple linkbylink scheduling, we consider the problem of sequential relay placement so as to minimize the expectation of an endtoend cost metric (a linear combination of the sum of convex hop costs and the number of relays placed). This impromptu relay placement problem is formulated as a total cost Markov decision process.
Optimal Sequential Wireless Relay Placement on a Random Lattice Path
"... Abstract—Our work is motivated by the need for impromptu (or “asyougo”) deployment of relay nodes (for establishing a packet communication path with a control centre) by firemen/commandos while operating in an unknown environment. We consider a model, where a deployment operative steps along a ra ..."
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Abstract—Our work is motivated by the need for impromptu (or “asyougo”) deployment of relay nodes (for establishing a packet communication path with a control centre) by firemen/commandos while operating in an unknown environment. We consider a model, where a deployment operative steps along a random lattice path whose evolution is Markov. At each step, the path can randomly either continue in the same direction or take a turn “North ” or “East, ” or come to an end, at which point a data source (e.g., a temperature sensor) has to be placed that will send packets to a control centre at the origin of the path. A decision has to be made at each step whether or not to place a wireless relay node. Assuming that the packet generation rate by the source is very low, and simple linkbylink scheduling, we consider the problem of relay placement so as to minimize the expectation of an endtoend cost metric (a linear combination of the sum of convex hop costs and the number of relays placed). This impromptu relay placement problem is formulated as a total cost Markov decision process. First, we derive the optimal policy in terms of an optimal placement set and show that this set is characterized by a boundary beyond which it is optimal to place. Next, based on a simpler alternative onesteplookahead characterization of the optimal policy, we propose an algorithm which is proved to converge to the optimal placement set in a finite number of steps and which is faster than the traditional value iteration. We show by simulations that the distance based heuristic, usually assumed in the literature, is close to the optimal provided that the threshold distance is carefully chosen.