In multiagent surveillance missions, a group of agents monitors some points of interest to provide situational awareness. For agents with local communication capabilities, one way to transmit the surveillance information to a base is streaming by the instantaneous data via multihop communications over a connected network. However, a connected communication network may become disconnected if some agents leave the surveillance area (for example, for refueling). This paper presents a locally applicable, efficient, and scalable strategy that guarantees a connected communication network between the base and the agents in the face of any agent removal. The proposed decentralized strategy is based on a sequence of local replacements, which are initiated by the agent leaving the network. It is shown that the replacement sequence always ends with the relocation of an agent, for which the absence from its current position does not disconnect the network. Furthermore, the optimality (that is, the minimum number of r...
Different from the previous studies, @cite_18 , @cite_17 , @cite_4 and @cite_12 consider mobile agents and propose some agent movements for connectivity restoration of wireless sensor networks in agent failure. In @cite_18 , a distributed control algorithm is introduced for connectivity maintenance. Before any failure, the algorithm runs and identifies all critical agents, whose failure will cause network disconnection. Then, it assigns required actions to each agent in advance. The studies in @cite_17 and @cite_4 differ from @cite_18 by maintaining connectivity through some agent relocations initiated by the failing agent. In @cite_4 , the authors present a centralized algorithm as an alternative to the decentralized scheme given in @cite_17 , which is not always feasible in general graphs. Finally, the authors of @cite_12 use the shortest path routing table in their algorithm, and they propose a distributed recovery mechanism that maintains the network connectivity with minimal topology change, i.e. not increasing the length of the shortest path between any arbitrary two agents after the reconfiguration.
@cite_18 @cite_4 @cite_12 @cite_17
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Designing robust algorithms for mobile agents with reliable communication is difficult due to the distributed nature of computation, in mobile ad hoc networks (MANETs) the matter is exacerbated by the need to ensure connectivity. Existing distributed algorithms provide coordination but typically assume connectivity is ensured by other means. We present a connectivity service that encapsulates an arbitrary motion planner and can refine any plan to preserve connectivity (the graph of agents remains connected) and ensure progress (the agents advance towards their goal). The service is realized by a distributed algorithm that is modular in that it makes no assumptions of the motion-planning mechanism except the ability for an agent to query its position and intended goal position, local in that it uses 1-hop broadcast to communicate with nearby agents but doesn't need any network routing infrastructure, and oblivious in that it does not depend on previous computations. We prove the progress of the algorithm in one round is at least Ω(min(d, r)), where d is the minimum distance between an agent and its target and r is the communication radius. We characterize the worst case configuration and show that when d ≥ r this bound is tight and the algorithm is optimal, since no algorithm can guarantee greater progress. Finally we show all agents get Ɛ-close to their targets within O(D0 r+n2 Ɛ) rounds where n is the number of agents and D0 is the sum of the initial distances to the targets. Control of mobile networks raises fundamental and novel problems in controlling the structure of the resulting dynamic graphs. In particular, in applications involving mobile sensor networks and multi-agent systems, a great new challenge is the development of distributed motion algorithms that guarantee connectivity of the overall network. In this paper, we address this challenge using a novel control decomposition. First, motion control is performed in the continuous state space, where nearest neighbor potential fields are used to maintain existing links in the network. Second, distributed coordination protocols in the discrete graph space ensure connectivity of the switching network topology. Coordination is based on locally updated estimates of the abstract network topology by every agent as well as distributed auctions that enable tie breaking whenever simultaneous link deletions may violate connectivity. Integration of the overall system results in a distributed, multi- agent, hybrid system for which we show that, under certain secondary objectives on the agents and the assumption that the initial network is connected, the resulting motion always satisfies connectivity of the network. Our approach can also account for communication time delays in the network as well as collision avoidance, while its efficiency and scalability properties are illustrated in nontrivial computer simulations. A distributed control law that guarantees connectivity maintenance in a network of multiple mobile agents is presented. The control law, which lets the agents perform formation manoeuvres, respects sensor limitations by allowing each agent to only take into account agents within its sensing radius. In contrast to previous approaches to the problem, the proposed control law does not attain infinite values whenever an edge of the communication graph tends to be lost. This is achieved via the use of decentralised navigation functions, which are bounded potential fields. The navigation functions are defined to take into account the connectivity maintenance objective. The authors first treat the case of connectivity maintenance for a static communication graph and then extend the result to the case of dynamic graphs. The results are illustrated on a formation control problem. In this paper, we study the problem of reaching a consensus among all the agents in the networked control systems (NCS) in the presence of misbehaving agents. A reputation-based resilient distributed control algorithm is first proposed for the leader-follower consensus network. The proposed algorithm embeds a resilience mechanism that includes four phases (detection, mitigation, identification, and update), into the control process in a distributed manner. At each phase, every agent only uses local and one-hop neighbors' information to identify and isolate the misbehaving agents, and even compensate their effect on the system. We then extend the proposed algorithm to the leaderless consensus network by introducing and adding two recovery schemes (rollback and excitation recovery) into the current framework to guarantee the accurate convergence of the well-behaving agents in NCS. The effectiveness of the proposed method is demonstrated through case studies in multirobot formation control and wireless sensor networks.