A connectivity monitoring model of opportunistic sensor network based on evolving graph

Shu, Jian; Jiang, Shandong; Li, Qun; Liu, Linlan; Geng, Xiaotian

doi:10.2298/csis141023032s

Cited by 3 publications

(2 citation statements)

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“…The authors in Monteiro et al evaluated the performance of dynamic networks in terms of average throughput, average end‐to‐end delay, ratio of dropped packets by no route, and ratio of dropped packets by interface link queue overflow. In Ferreira et al the evolving graph has been employed to evaluate the performance of routing protocols of mobile ad hoc networks (MANETs) with known connectivity patterns, while Shu et al utilized it in their work for monitoring connectivity in opportunistic sensor network. As evolving graph model can effectively represent the topology changes in dynamic networks, therefore, we utilize it to model opportunistic multihop networks in our proposed work.…”

Section: Related Workmentioning

confidence: 99%

On computing the reliability of opportunistic multihop networks with Mobile relays

Khanna

Chaturvedi

Soh

2019

Quality & Reliability Eng

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Opportunistic multihop networks with mobile relays recently have drawn much attention from researchers across the globe due to their wide applications in various challenging environments. However, because of their peculiar intrinsic features like lack of continuous connectivity, network partitioning, highly dynamic behavior, and long delays, it is very arduous to model and effectively capture the temporal variations of such networks with the help of classical graph models. In this work, we utilize an evolving graph to model the dynamic network and propose a matrix‐based algorithm to generate all minimal path sets between every node pair of such network. We show that these time‐stamped‐minimal‐path sets (TS‐MPS) between each given source‐destination node pair can be used, by utilizing the well‐known Sum‐of‐Disjoint Products technique, to generate various reliability metrics of dynamic networks, ie, two‐terminal reliability of dynamic network and its related metrics, ie, two‐terminal reliabilities of the foremost, shortest, and fastest TS‐MPS, and Expected Hop Count. We also introduce and compute a new network performance metric−Expected Slot Count. We use two illustrative examples of dynamic networks, one of four nodes, and the other of five nodes, to show the salient features of our technique to generate TS‐MPS and reliability metrics.

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Section: Related Workmentioning

confidence: 99%

On computing the reliability of opportunistic multihop networks with Mobile relays

Khanna

Chaturvedi

Soh

2019

Quality & Reliability Eng

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“…In research, the time‐division topology of an inter‐satellite link network is a kind of graph evolving over time; this approach is a hot topic in computer science and widely used in dynamic network modeling . The evolving graph has been used to monitor the connectivity of opportunistic sensor networks . Additionally, the frequent change in the network topology has been found to be a potential challenge .…”

Section: Introductionmentioning

confidence: 99%

Time division inter‐satellite link topology generation problem: Modeling and solution

Chu

Chen

2017

Satell Commun Network

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In this paper, we study the time-division inter-satellite link topology generation (TDILTG) problem for the well-known Chinese BeiDou Global Navigation Satellite System. The TDILTG problem consists in generating a time-division topology of the inter-satellite link network for the navigation satellite system to spread systematic data to all satellites via a few source satellites with the purpose of minimizing the time required to spread the data. We propose a mathematical model to formulate the TDILTG problem and study its 2 lower bounds through a thorough analysis of the problem characteristics. We also present a deterministic constructive (DC) algorithm to solve this problem approximately but very quickly, with a time complexity of O(n 3 ), where n is the number of satellites. Extensive experimental studies on a wide range of randomly generated instances show that the proposed DC algorithm is able to obtain the optimal solutions for most tested instances in less than 1 second. Meanwhile, we also validate that the DC algorithm performs well when the problem scale is large. Furthermore, we provide insights of the effects of different instance parameters on the final results. KEYWORDS combinatorial optimization, global navigation satellite system, heuristics algorithm, topology generation 1 | INTRODUCTION One of the most important issues for the inter-satellite link network management of the well-known Chinese Global Navigation Satellite System 1 is how to generate a topology of the inter-satellite link network in a time-division multiplexing transmission mode. This leads to an interesting optimization problem that we named the time-division inter-satellite link topology generation (TDILTG) problem. The purpose of this problem is to generate a topology that minimizes the period of time required for spreading data 1 while satisfying a set of transmission constraints.To make a low-power and large-scale inter-satellite link network, 2 the global Navigation Satellite System uses the time-division transmission mode to establish inter-satellites links, where the time horizon is divided into several slots. In each slot, each satellite connects to another satellite, and each satellite switches to another satellite in the next slot. It is thus appropriate to use an evolving graph to represent the topology of the intersatellite link network, where the edges of the graph evolve over time. In the meantime, ground stations need to transmit systematic data to all satellites via limited source satellites, and each satellite is expected to receive the data as soon as possible.Furthermore, each satellite in a pair of satellites having a connection must remain visible to the other within the effective time domain of the topology. Because the visibility relation of 2 satellites may change over time because of the relative motion of the satellites, the navigation system needs to generate the topology of the network every once in a while. It is thus necessary for the system to solve the problem automatically and effectively to meet the...

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An Improved Opportunistic Sensor Networks Connectivity Monitoring Model Based on Network Connectivity

Shu

Jia-jun

et al. 2019

Communications in Computer and Information Science

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A connectivity monitoring model of opportunistic sensor network based on evolving graph

Cited by 3 publications

References 0 publications

On computing the reliability of opportunistic multihop networks with Mobile relays

On computing the reliability of opportunistic multihop networks with Mobile relays

Time division inter‐satellite link topology generation problem: Modeling and solution

An Improved Opportunistic Sensor Networks Connectivity Monitoring Model Based on Network Connectivity

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