A system of simultaneously triggered clocks is designed to be stabilizing: if the clock values ever differ, the system is guaranteed to converge to a state where all clock values are identical, and are subsequently ma...
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A system of simultaneously triggered clocks is designed to be stabilizing: if the clock values ever differ, the system is guaranteed to converge to a state where all clock values are identical, and are subsequently maintained to be identical. For an N-clock system, the design uses N registers of 2 log N bits each and guarantees convergence to identical values within N 2 "triggers".
A coterie is a set of quorums such that any two quorums intersect each other, and is used in a quorum based algorithm for solving the mutual exclusion problem. The availability of a coterie is the probability that the...
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A coterie is a set of quorums such that any two quorums intersect each other, and is used in a quorum based algorithm for solving the mutual exclusion problem. The availability of a coterie is the probability that the algorithm (adopting the coterie) tolerates process and/or link failures. Constructing an optimal coterie in terms of the availability is therefore important from the view of fault tolerance, but unfortunately, even calculating the availability is known to be #P-hard. Recently Harada and Yamashita proposed several heuristic methods for improving the availability of a coterie. This letter first evaluates their performance and then proposes a practical method for constructing a semi-optimal coterie by using one of the heuristic methods as a main component.
Navigation with wireless sensor networks (WSNs) is the key to provide an effective path for the mobile node. Without any location information, the path planning algorithm generates a big challenge. Many algorithms pro...
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Navigation with wireless sensor networks (WSNs) is the key to provide an effective path for the mobile node. Without any location information, the path planning algorithm generates a big challenge. Many algorithms provided efficient paths based on tracking sensor nodes which forms a competitive method. However, most previous works have overlooked the distance cost of the path. In this paper, the problem is how to obtain a path with minimum distance cost and effectively organize the network to ensure the availability of this path. We first present a distributed algorithm to construct a path planning infrastructure by uniting the neighbors' information of each sensor node into an improved connected dominating set. Then, a path planning algorithm is proposed which could produce a path with its length at most c times the shortest Euclidean length from initial position to destination. We prove that the distributed algorithm has low time and message complexity and c is no more than a constant. Under different deployed environments, extensive simulations evaluate the effectiveness of our work. The results show that factor c is within the upper bound proved in this paper and our distributed algorithm achieves a smaller infrastructure size.
In wireless sensor networks, since sensor nodes are distributed in inaccessible regions for data gathering, they need to be operated during an assigned time without battery recharging and relocation. For this reason, ...
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In wireless sensor networks, since sensor nodes are distributed in inaccessible regions for data gathering, they need to be operated during an assigned time without battery recharging and relocation. For this reason, there has been abundant research on improving energy efficiency. PEGASIS, one of the well-known chain-based routing protocols for improving energy efficiency, builds a chain based on the greedy algorithm. However, due to long communication distance of some sensor nodes in a chain formed by the greedy algorithm, unbalanced energy consumption of sensor nodes occurs. Eventually, the network lifetime from this cause decreases. We propose energy efficient chain formation (EECF) algorithm to resolve the unbalanced energy consumption problem caused by long-distance data transmission of some nodes in a chain formed by the greedy algorithm. The simulation results are used to verify the energy consumption balance of sensor nodes and the whole network lifetime. In simulation, it is shown that EECF produces better results than the greedy algorithm.
Consider k robots initially located at a point inside a region T. Each robot can move anywhere in T independently of the other robots with maximum speed one. The goal of the robots is to evacuate T through an exit at ...
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Consider k robots initially located at a point inside a region T. Each robot can move anywhere in T independently of the other robots with maximum speed one. The goal of the robots is to evacuate T through an exit at an unknown location on the boundary of T. The objective is to minimize the evacuation time, which is defined as the time the last robot reaches the exit. We consider the face-to-face communication model for the robots: a robot can communicate with another robot only when they meet in T. In this paper, we give upper and lower bounds for the face-to-face evacuation time by k robots that are initially located at the centroid of a unit-sided equilateral triangle or square. For the case of a triangle with k = 2 robots, we give a lower bound of 1 + 2/root 3 approximate to 2.154, and an algorithm with upper bound of 2.3367 on the worst-case evacuation time. We show that for any k, any algorithm for evacuating k >= 2 robots requires at least root 3 time. This bound is asymptotically optimal, as we show that even a straightforward strategy of evacuation by k robots gives an upper bound of root 3 + 3/k. For k = 3 and 4, we give better algorithms with evacuation times of 2.0887 and 1.9816, respectively. For the case of the square and k = 2, we give an algorithm with evacuation time of 3.4645 and show that any algorithm requires time at least 3.118 to evacuate in the worst-case. Moreover, for k = 3, and 4, we give algorithms with evacuation times 3.1786 and 2.6646, respectively. The algorithms given for k = 3 and 4 for evacuation in the triangle or the square can be easily generalized for larger values of k. (C) 2020 Elsevier B.V. All rights reserved.
In this paper we study the distributed average consensus problem in multi-agent systems with dynamically-changing directed communication links that are subject to quantized information flow. We present and analyze a d...
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In this paper we study the distributed average consensus problem in multi-agent systems with dynamically-changing directed communication links that are subject to quantized information flow. We present and analyze a distributed averaging algorithm which operates exclusively with quantized values (i.e., the information stored, processed and exchanged between neighboring agents is subject to deterministic uniform quantization) and relies on event-driven updates (e.g., to reduce energy con-sumption, communication bandwidth, network congestion, and/or processor usage). We characterize the properties of the proposed distributed algorithm over dynamic directed communication topologies subject to some connectivity conditions and we show that its execution allows each agent to reach, in finite time, a fixed state that is equal (within one quantization level) to the average of the initial states. The main idea of the proposed algorithm is that each agent (i) models its initial state as two quantized fractions which have numerators equal to the agent's initial state and denominators equal to one, and (ii) transmits one fraction randomly while it keeps the other stored. Then, every time an agent receives one or more fractions, it averages their numerators with the numerator of the fraction it stored, and then transmits them to randomly selected out-neighbors. Finally, we provide examples to illustrate the operation, performance, and potential advantages of the proposed algorithm. We compare against various quantized average consensus algorithms and show that our algorithm's convergence speed is among the fastest in the current literature.(c) 2022 Published by Elsevier Ltd.
Virtual Reality (VR) is becoming an important use case for 5G wireless networks, and Mobile Edge Computing (MEC) servers are being explored as a way to reduce VR video latency. To address the limited cache space of a ...
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Virtual Reality (VR) is becoming an important use case for 5G wireless networks, and Mobile Edge Computing (MEC) servers are being explored as a way to reduce VR video latency. To address the limited cache space of a single MEC server, this paper proposes dividing geographically close MEC servers into collaborative domains. A new VR video transmission architecture is designed after analyzing video compression *** proposed architecture splits the VR video into equal-sized tile files to simplify the cache problem and improve caching efficiency. However, the large number of different tile files presents a challenge. To address this, the paper proposes an optimized k-shortest paths (OKSP) algorithm with a time complexity of O((K & BULL;M+N)& BULL;M & BULL;log N), where K is the number of tiles that all M MEC servers can cache in the collaboration domain and N is the number of tile files. For extremely large-scale data cases, a greedy-based approximation algorithm is also proposed. The numerical results demonstrate the OKSP algorithm's excellent performance in solving large-scale data, outperforming other caching algorithms in experiments.
This article presents an algorithm for constructing a spanner for ad hoc networks whose nodes have variable transmission range. Almost all previous spanner constructions for ad hoc networks assumed that all nodes in t...
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This article presents an algorithm for constructing a spanner for ad hoc networks whose nodes have variable transmission range. Almost all previous spanner constructions for ad hoc networks assumed that all nodes in the network have the same transmission range. This allowed a succinct representation of the network as a unit disk graph, serving as the basis for the construction. In contrast, when nodes have variable transmission range, the ad hoc network must be modeled by a general disk graph. Whereas unit disk graphs are undirected, general disk graphs are directed. This complicates the construction of a spanner for the network, since currently there are no efficient constructions of low-stretch spanners for general directed graphs. Nevertheless, in this article it is shown that the class of disk graphs enjoys (efficiently constructible) spanners of quality similar to that of unit disk graph spanners. Moreover, it is shown that the new construction can be performed in a localized fashion. Our results use only simple packing arguments, hence all algorithms work for every metric space of constant doubling dimension.
We consider the problem of computing the optimal swap edges of a shortest-path tree. This problem arises in designing systems that offer point-of-failure shortest-path rerouting service in presence of a single link fa...
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We consider the problem of computing the optimal swap edges of a shortest-path tree. This problem arises in designing systems that offer point-of-failure shortest-path rerouting service in presence of a single link failure: if the shortest path is not affected by the failed link, then the message will be delivered through that path;other-wise, the system will guarantee that, when the message reaches the node where the failure has occurred, the message will then be re-routed through the shortest detour to its destination. There exist highly efficient serial solutions for the problem, but unfortunately because of the structures they use, there is no known (nor foreseeable) efficient distributed implementation for them. A distributed protocol exists only for finding swap edges, not necessarily optimal ones. We present two simple and efficient distributed algorithms for computing the optimal swap edges of a shortest-path tree. One algorithm uses messages containing a constant amount of information, while the other is tailored for systems that allow long messages. The amount of data transferred by the protocols is the same and depends on the structure of the shortestpath spanning-tree;it is no more, and sometimes significantly less, than the cost of constructing the shortest-path tree.
In modern technologies, the industrial internet of things (IIoT) has gained rapid growth in the fields of medical, transportation, and engineering. It consists of a self-governing configuration and cooperated with sen...
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In modern technologies, the industrial internet of things (IIoT) has gained rapid growth in the fields of medical, transportation, and engineering. It consists of a self-governing configuration and cooperated with sensors to collect, process, and analyze the processes of a real-time system. In the medical system, healthcare IIoT (HIIoT) provides analytics of a huge amount of data and offers low-cost storage systems with the collaboration of cloud systems for the monitoring of patient information. However, it faces certain connectivity, nodes failure, and rapid data delivery challenges in the development of e-health systems. Therefore, to address such concerns, this paper presents an efficient data uncertainty management model for HIIoT using machine learning (EDM-ML) with declining nodes prone and data irregularity. Its aim is to increase the efficacy for the collection and processing of real-time data along with smart functionality against anonymous nodes. It developed an algorithm for improving the health services against disruption of network status and overheads. Also, the multi-objective function decreases the uncertainty in the management of medical data. Furthermore, it expects the routing decisions using a machine learning-based algorithm and increases the uniformity in health operations by balancing the network resources and trust distribution. Finally, it deals with a security algorithm and established control methods to protect the distributed data in the exposed health industry. Extensive simulations are performed, and their results reveal the significant performance of the proposed model in the context of uncertainty and intelligence than benchmark algorithms.
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