Recent improvements in nanotechnology and Internet of Things (IoT) have led to the emergence of the concept of Internet of Nano-Things (IoNT). This concept provided ease of access and communication facilities for the ...
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Recent improvements in nanotechnology and Internet of Things (IoT) have led to the emergence of the concept of Internet of Nano-Things (IoNT). This concept provided ease of access and communication facilities for the nano-devices in applications of different fields operating at the molecular level such as health, industry, agriculture, robotics and military. These distributed devices interconnect over the Wireless Nano-Sensor Networks (WNSNs) in nano-scale which have limited energy and capacity. Therefore, these devices need to use their energy efficiently when communicating with each other to ensure network continuity and maintain all processes of IoNT applications. In this paper, a novel energy-efficient distributed routing algorithm, namely DEEPNT, is proposed in order to extend the lifetime of WNSNs in IoNT applications. The communication backbone of WNSNs constructed by DEEPNT by selecting cluster head nodes can be used in all types of IoNT applications in nano-scale in order to provide continuous data flow in critical areas such as healthcare running in vivo. This novel energy-efficient distributed protocol is compared with the traditional flooding based method and with an energy aware routing algorithm. According to the results, DEEPNT prolongs the WNSNs average lifetime respectively up to 10.78 and 5.95 times compared to mentioned algorithms despite the larger network sizes in nano-scale.(C) 2022 Elsevier B.V. All rights reserved.
The privacy-preserving data publishing (PPDP) problem has gained substantial attention from research communities, industries, and governments due to the increasing requirements for data publishing and concerns about d...
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The privacy-preserving data publishing (PPDP) problem has gained substantial attention from research communities, industries, and governments due to the increasing requirements for data publishing and concerns about data privacy. However, achieving a balance between preserving privacy and maintaining data quality remains a challenging task in PPDP. This paper presents an information-driven distributed genetic algorithm (ID-DGA) that aims to achieve optimal anonymization through attribute generalization and record suppression. The proposed algorithm incorporates various components, including an information-driven crossover operator, an information-driven mutation operator, an information-driven improvement operator, and a two-dimensional selection operator. Furthermore, a distributed population model is utilized to improve population diversity while reducing the running time. Experimental results confirm the superiority of ID-DGA in terms of solution accuracy, convergence speed, and the effectiveness of all the proposed components.
The class of CRC constraints generalizes several tractable classes of constraints and is expressive enough to model problems in domains such as temporal reasoning, geometric reasoning, and scene labelling. This paper ...
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The class of CRC constraints generalizes several tractable classes of constraints and is expressive enough to model problems in domains such as temporal reasoning, geometric reasoning, and scene labelling. This paper presents the first distributed deterministic algorithm for connected row-convex (CRC) constraints. Our distributed (partial) path consistency algorithm efficiently transforms a CRC constraint network into an equivalent constraint network, where all constraints are minimal (i.e., they are the tightest constraints) and generating all solutions can be done in a backtrack-free manner. When compared with the state-of-the-art distributed algorithm for CRC constraints, which is a randomized one, our algorithm guarantees to generate a solution for satisfiable CRC constraint networks and it is applicable to solve large networks in real distributed systems. The experimental evaluations show that our algorithm outperforms the state-of-the-art algorithm in both practice and theory.
We propose a new distributed delay-constrained unicast routing algorithm which can always find a delay-constrained path with small message complexity if such a path exists. At each network node, limited information ab...
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We propose a new distributed delay-constrained unicast routing algorithm which can always find a delay-constrained path with small message complexity if such a path exists. At each network node, limited information about the network state is needed and only a small amount of computation is required. Simulation results show that the proposed algorithm has much better cost performance than the least delay path algorithm. (C) 1998 Elsevier Science B.V.
Inner product operation of vector is a very common method in signal processing,especially in digital filter,and there is a great influence of calculating speed and the occupied resources upon the signal processing sys...
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Inner product operation of vector is a very common method in signal processing,especially in digital filter,and there is a great influence of calculating speed and the occupied resources upon the signal processing system.A traditional serial shift-summation distributed algorithm(DA)needs many shift-summation operations but not high in the calculating speed,and complete pipeline parallel structure needs many chip resources of Field Programmable Gates Array(FPGA).For these reasons,an improved method was presented,in which Multi-Port Read Only Memory(MPROM)was synthesized by a Look-Up Table in FPGA to construct a distributed ***'s more,logic shift operation is replaced by Zero-Padding as to reduce resource occupation and calculation time *** verification by simulation and synthesization,it was shown that the improved algorithm can reach the performance of a complete pipeline parallel structure but only needs a resource occupation of the serial shift-summation structure.
Demand response has recently become a topic of active research. Most of work however considers only the balance between aggregate load and supply, and abstracts away the underlying power network. In this paper, we stu...
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ISBN:
(纸本)9781467350501
Demand response has recently become a topic of active research. Most of work however considers only the balance between aggregate load and supply, and abstracts away the underlying power network. In this paper, we study demand response in a radial distribution network, by formulating it as an optimal power flow problem that maximizes the aggregate user utilities and minimizes the supply cost and the power line losses, subject to the power flow constraints and operating constraints. We propose a fully distributed algorithm for the users to coordinate their demand response decisions through local communication with their neighbors so as to achieve the optimum. Numerical examples with the real-world distribution circuits are provided to complement our theoretical analysis.
In this paper, we propose a set cover game and show that any Nash equilibrium is a minimal set cover, and also a Pareto optimal solution. Then we present a distributed algorithm to realize the game. The algorithm is s...
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In this paper, we propose a set cover game and show that any Nash equilibrium is a minimal set cover, and also a Pareto optimal solution. Then we present a distributed algorithm to realize the game. The algorithm is self-organizing in the sense that all players can make decisions by themselves simultaneously. It is local in the sense that each player makes his decision based only on information in his neighborhood. It is efficient in the sense that it converges to a minimal set cover in polynomial time when c(max)/c(min) is upper bounded by a polynomial of the input size, where c(max) and c(min) are the maximum cost and the minimum cost of sets, respectively.
In this paper, we introduce the architecture of LEO satellite network first of all, and then conduct a research on a classical distributed algorithm "Datagram Routing algorithm"(DRA) for LEO satellite networ...
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ISBN:
(纸本)9780769547923
In this paper, we introduce the architecture of LEO satellite network first of all, and then conduct a research on a classical distributed algorithm "Datagram Routing algorithm"(DRA) for LEO satellite network. Our core work focus on optimizing the DRA and giving a corresponding rerouting strategy for optimized algorithm. Finally some simulation experiments evaluating the performance of our novel algorithm and re-routing strategy are demonstrated.
Cooperative and distributed relocation strategy of multi-robot systems is a critical matter in self-reconfigurable modular robotic systems. In this paper, we depict a flexible distributed redeployment algorithm to rel...
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ISBN:
(纸本)9781467360265
Cooperative and distributed relocation strategy of multi-robot systems is a critical matter in self-reconfigurable modular robotic systems. In this paper, we depict a flexible distributed redeployment algorithm to relocate a large collection of micro-robots according to a list of desired final positions. Our algorithm is based on novel mechanisms reducing the need for global synchronization. The focus is made on the cooperative aspects that control all robots, each one animated by an individual objective, and collaborates in order to achieve the relocation objective. We show results from simulations on an open source multi-robot simulator.
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