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We are motivated by the need, in some applications, for impromptu or as-you-go deployment of wireless sensor networks. A person walks along a line, making link quality measurements with the previous relay at equally spaced locations, and... more
We are motivated by the need, in some applications, for impromptu or as-you-go deployment of wireless sensor networks. A person walks along a line, making link quality measurements with the previous relay at equally spaced locations, and deploys relays at some of these locations, so as to connect a sensor placed on the line with a sink at the start of the line. In this paper, we extend our earlier work on the problem (see [1]) to incorporate two new aspects: (i) inclusion of path outage in the deployment objective, and (ii) permitting the deployment agent to make measurements over several consecutive steps before selecting a placement location among them (which we call backtracking). We consider a light traffic regime, and formulate the problem as a Markov decision process. Placement algorithms are obtained for two cases: (i) the distance to the source is geometrically distributed with known mean, and (ii) the average cost per step case. We motivate the per-step cost function in ter...
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Our work is motivated by geographical forwarding of sporadic alarm packets to a base station in a wireless sensor network (WSN), where the nodes are sleep-wake cycling periodically and asynchronously. When a node (referred to as the... more
Our work is motivated by geographical forwarding of sporadic alarm packets to a base station in a wireless sensor network (WSN), where the nodes are sleep-wake cycling periodically and asynchronously. When a node (referred to as the source) gets a packet to forward, either by detecting an event or from an upstream node, it has to wait for its neighbors in a forwarding set (referred to as relays) to wake-up. Each of the relays is associated with a random reward (e.g., the progress made towards the sink) that is iid. To begin with, the source is uncertain about the number of relays, their wake-up times and the reward values, but knows their distributions. At each relay wake-up instant, when a relay reveals its reward value, the source's problem is to forward the packet or to wait for further relays to wake-up. In this setting, we seek to minimize the expected waiting time at the source subject to a lower bound on the average reward. In terms of the operations research literature,...
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Research Interests: Computer Science, Distributed Computing, Telecommunications, Broadband, Computer Network, and 13 moreSystem Architecture, Broadband Networks, Phy, Wimax, Directional Antenna, Reuse, IEEE Communications Magazine, Rural Area, Broadband Access, Communications, Electrical And Electronic Engineering, Single Channel, and Spatial reuse
Research Interests: Computer Science, Distributed Computing, Congestion Control, Adaptive Control, Performance, and 15 moreMarkov Processes, Packet Switching, Adaptive Systems, Computer Network, Protocols, Feedback, Local Area Networks, asynchronous Transfer Mode, Delays, Markov chain, Network Model, Bandwidth, Bottleneck, Channel Capacity, and Propagation delay
Research Interests: Mathematics, Computer Science, Distributed Computing, Network Analysis, Probability, and 15 moreStochastic processes, Computer Network, Wireless Network, Ad Hoc Networks, Throughput, Single Cell, Wireless Lan, asymptotic Analysis, Perforation, Wireless Application Protocol, MAC Protocol, Transport Protocols, Performance Measure, Markov model, and fixed point
Abstract: We study the problem of wireless sensor network design by deploying a minimum number of\ emph {additional} relay nodes (to minimize network cost) at a subset of\ emph {given potential} relay locations, in order to convey the... more
Abstract: We study the problem of wireless sensor network design by deploying a minimum number of\ emph {additional} relay nodes (to minimize network cost) at a subset of\ emph {given potential} relay locations, in order to convey the data from already existing sensor ...
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Résumé: Numerous algorithms and techniques for optimal performance of an IEEE 802.11 WLAN have been investigated by researchers. These algorithms make use of either power control or PHY (physical layer) rate control (ie, adaptive... more
Résumé: Numerous algorithms and techniques for optimal performance of an IEEE 802.11 WLAN have been investigated by researchers. These algorithms make use of either power control or PHY (physical layer) rate control (ie, adaptive selection of PHY rates) or both to achieve maximum throughput levels for the network at minimum power consumption by the mobile devices. However most of these techniques are non-cooperative by definition (ie, they attempt to maximize an individual node's performance and not the overall network ...
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In geographical forwarding of packets in a large wireless sensor network (WSN) with sleep-wake cycling nodes, we are interested in the local decision problem faced by a node that has “custody” of a packet and has to choose one among a set... more
In geographical forwarding of packets in a large wireless sensor network (WSN) with sleep-wake cycling nodes, we are interested in the local decision problem faced by a node that has “custody” of a packet and has to choose one among a set of next-hop relay nodes to forward the packet toward the sink. Each relay is associated with a “reward” that summarizes the benefit of forwarding the packet through that relay. We seek a solution to this local problem, the idea being that such a solution, if adopted by every node, could provide a reasonable heuristic for the end-to-end forwarding problem. Toward this end, we propose a local relay selection problem consisting of a forwarding node and a collection of relay nodes, with the relays waking up sequentially at random times. At each relay wake-up instant, the forwarder can choose to probe a relay to learn its reward value, based on which the forwarder can then decide whether to stop (and forward its packet to the chosen relay) or to continu...
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We study the trade-off between delivery delay and energy consumption in a delay tolerant network in which a message (or a file) has to be delivered to each of several destinations by epidemic relaying. In addition to the destinations,... more
We study the trade-off between delivery delay and energy consumption in a delay tolerant network in which a message (or a file) has to be delivered to each of several destinations by epidemic relaying. In addition to the destinations, there are several other nodes in the network that can assist in relaying the message. We first assume that, at every instant, all the nodes know the number of relays carrying the packet and the number of destinations that have received the packet. We formulate the problem as a controlled ...
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Research Interests: Engineering, Resource Allocation, Wireless Network, Cellular Network, Sensor Network, and 12 moreRadio Frequency, Physical Layer, Random Networks, Spectrum, Wireless Sensor, Random Access, Cross layer, Access Point, Sadhana, Wireless Sensor Network, Code Division Multiple Access, and Scheduling Algorithm
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Abstract. We consider the problem of quickest transient change detection under a Bayesian setting. The change occurs at a random time Γ1 and disappears at a random time Γ2 > Γ1. Thus, at any time k, the system can be in one of the... more
Abstract. We consider the problem of quickest transient change detection under a Bayesian setting. The change occurs at a random time Γ1 and disappears at a random time Γ2 > Γ1. Thus, at any time k, the system can be in one of the following states, i) prechange, ii) in ...
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ABSTRACT A person walks along a line (which could be an idealisation of a forest trail, for example), placing relays as he walks, in order to create a multihop network for connecting a sensor at a point along the line to a sink at the... more
ABSTRACT A person walks along a line (which could be an idealisation of a forest trail, for example), placing relays as he walks, in order to create a multihop network for connecting a sensor at a point along the line to a sink at the start of the line. The potential placement points are equally spaced along the line, and at each such location the decision to place or not to place a relay is based on link quality measurements to the previously placed relays. The location of the sensor is unknown apriori, and is discovered as the deployment agent walks. In this paper, we extend our earlier work on this class of problems to include the objective of achieving a 2-connected multihop network. We propose a network cost objective that is additive over the deployed relays, and accounts for possible alternate routing over the multiple available paths. As in our earlier work, the problem is formulated as a Markov decision process. Placement algorithms are obtained for two source location models, which yield a discounted cost MDP and an average cost MDP. In each case we obtain structural results for an optimal policy, and perform a numerical study that provides insights into the advantages and disadvantages of multi-connectivity. We validate the results obtained from numerical study experimentally in a forest-like environment
AbstractThis work is motivated by the idea of using randomly deployed wireless networks of miniature smart sensors to serve as distributed instrumentation. In such applications, often the objective of the sensor network is to repeatedly... more
AbstractThis work is motivated by the idea of using randomly deployed wireless networks of miniature smart sensors to serve as distributed instrumentation. In such applications, often the objective of the sensor network is to repeatedly compute and, if required, deliver to an ...
Research Interests: Distributed Computing, Wireless Sensor Networks, Optimization Problem, Wireless Network, Ad Hoc Networks, and 10 morePerformance Improvement, Sensor Network, Self Organization, Random Access, Distributed Optimization, Wireless Sensor Network, Intelligent Sensors, Stochastic Algorithm, Complex I, and Distributed Algorithm
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Research Interests: Optimal Control, Iterative Methods, Scheduling, Markov Processes, Markov Decision Process, and 15 moreWireless Network, Physical Layer, Value Iteration, Rate Control, Structural Properties, Medium Access Control, Cross layer, Cost Function, Electrical And Electronic Engineering, Base station, Fading channels, Markov model, Channel State Information, Optimal scheduling, and Queue length
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ABSTRACT The work in this paper is motivated by the idea of using randomly deployed, ad hoc wireless networks of miniature smart sensors to serve as distributed instrumentation. We argue that in such applications it is important for the... more
ABSTRACT The work in this paper is motivated by the idea of using randomly deployed, ad hoc wireless networks of miniature smart sensors to serve as distributed instrumentation. We argue that in such applications it is important for the sensors to self-organise in a way that optimizes network throughput. We then identify and discuss two main problems of optimal selforganisation: (i) building an optimal topology, and (ii) tuning network access parameters such as the transmission attempt rate. We consider a simple random access model for sensor networks and formulate these problems as optimisation problems. We then present centralized as well as distributed algorithms for solving them. Results show that the performance improvement is substantial and implementation of such optimal self-organisation techniques may be worth the additional complexity.
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ABSTRACT In this paper, we study a problem of designing a multi-hop wireless network for interconnecting sensors (hereafter called source nodes) to a Base Station (BS), by deploying a minimum number of relay nodes at a subset of given... more
ABSTRACT In this paper, we study a problem of designing a multi-hop wireless network for interconnecting sensors (hereafter called source nodes) to a Base Station (BS), by deploying a minimum number of relay nodes at a subset of given potential locations, while meeting a quality of service (QoS) objective specified as a hop count bound for paths from the sources to the BS. The hop count bound suffices to ensure a certain probability of the data being delivered to the BS within a given maximum delay under a light traffic model. We observe that the problem is NP-Hard. For this problem, we propose a polynomial time approximation algorithm based on iteratively constructing shortest path trees and heuristically pruning away the relay nodes used until the hop count bound is violated. Results show that the algorithm performs efficiently in various randomly generated network scenarios; in over 90% of the tested scenarios, it gave solutions that were either optimal or were worse than optimal by just one relay. We then use random graph techniques to obtain, under a certain stochastic setting, an upper bound on the average case approximation ratio of a class of algorithms (including the proposed algorithm) for this problem as a function of the number of source nodes, and the hop count bound. To the best of our knowledge, the average case analysis is the first of its kind in the relay placement literature. Since the design is based on a light traffic model, we also provide simulation results (using models for the IEEE 802.15.4 physical layer and medium access control) to assess the traffic levels up to which the QoS objectives continue to be met.