GTS-based communication task scheduling for quantized output consensus over IEEE 802.15.4 wireless networks

Based on PD and PI control methods, the lag output consensus problem for second-order nonlinear multiagent systems (MASs) without and with external disturbances is addressed, which generalizes the existing lag consensus results for MASs. Firstly, a lag output consensus condition is derived for the MAS by designing a proper PD control scheme. Furthermore, a PI control strategy is developed to ensure that the MAS realizes the lag output consensus. In addition, two lag <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${\mathcal {H}}_{\infty } $ </tex-math></inline-formula> output consensus criteria are also established on the basis of PD and PI control schemes for the MAS with external disturbances. Lastly, two examples are utilized to verify the correctness and effectiveness of the devised control schemes. Note to Practitioners—Recently, virtual leader-based approach has been widely utilized to address the output consensus control problem for various MASs. Practically, each agent receiving its own output information may be later than the virtual leader. Therefore, it is more reasonable and meaningful to discuss the lag output consensus for MASs. Furthermore, considering that PID control is very simple and easy to implement, some PD and PI control strategies are developed to tackle the lag output consensus for MASs. In addition, since external disturbances are ubiquitous and may destroy the lag output consensus, the lag <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${\mathcal {H}}_{\infty } $ </tex-math></inline-formula> output consensus for MASs is also investigated. Multiple single-link robot systems experiments verify that the approaches given in this paper are feasible and valid.

Fractional Link scheduling is one of the most fundamental problems in wireless networks. The prevailing approach for shortest fractional link scheduling is based on a reduction to the maximum-weighted independent set problem, which itself may not admit efficient approximation algorithms. In addition, except for the wireless networks under the protocol interference model, none of the existing scheduling algorithms can produce a link schedule with explicit upper bounds on its length in terms of the link demands. As the result, the polynomial approximate capacity regions in these networks remain blank. This paper develops a purely combinatorial paradigm for fractional link scheduling in wireless networks. In addition to the superior efficiency, it is able to provide explicit upper bounds on the lengths of the produced link schedule. By exploiting these upper bounds, polynomial approximate capacity regions are derived. The effectiveness of this new paradigm is demonstrated by its applications in wireless networks under the physical interference model and wireless MIMO networks under the protocol interference model.

Leader–follower output consensus of multiagent systems over finite fields

Leader-following almost output consensus for discrete-time heterogeneous multi-agent systems in the presence of external disturbances

Achieving optimal transmission throughput in data networks is known as a fundamental but hard problem. The situation is exacerbated in multi-hop wireless networks due to the interference among local wireless transmissions. In this paper, we propose a general modeling and solution framework for the throughput optimization problem in wireless networks. In our framework, data routing, wireless medium contention and network coding are jointly considered to achieve the optimal network performance. The primal-dual solution method in the framework represents a cross-layer optimization approach. It decomposes the original problem into data routing sub-problems at the network layer, and power allocation sub-problems at the physical layer. Various effective solutions are discussed for each sub-problem, verifying that our framework may handle the throughput optimization problem in an efficient and distributed fashion for a broad range of wireless network scenarios.

SummaryThe cognitive radio network (CRN) is an emerging technology where communication among secondary users (SUs) takes place in an opportunistic manner. Since, a backbone eases the routing, reduces communication overhead, and efficiently handles the dynamic changes in the network. Therefore, we intend to propose a backbone formation algorithm in CRN. However, finding optimal backbone is equivalent to find minimum connected dominating set (CDS) for the given network, which is NP‐complete. Hence, the backbone construction problem can be better handled by optimization algorithms than the deterministic ones. The bio‐inspired is an interesting category of optimization algorithms. Therefore, it has been popularly used to handle various optimization problems in wireless networks. However, it has never been used for backbone construction in CRN. The ant colony optimization (ACO) is a promising bio‐inspired method because it has been effectively used to handle many problems in wireless networks, e.g. cluster head selection, leader election, routing etc. Therefore, we use ant colony system (ACS) for backbone formation in CRN. Also, the approach helps us to find optimized path between any pair of nodes to ensure efficient communication. To the best of our knowledge, it is the first bio‐inspired backbone construction algorithm in CRN.

In this paper, we study the output consensus problems for heterogeneous multi‐agent systems (MASs) with a high‐dimensional leader and directed topology, where the followers are subject to unknown uncertainties. First, an observer is designed to estimate leader's unmeasurable states. Then, by using neural network (NN) approximation theory, a neuro‐adaptive controller consists of a compensation part and a cooperative term is proposed. Unlike most existing neuro‐adaptive controllers that utilize some discontinuous functions to eliminate the effects of NN approximation errors, a new class of continuous function is used and thereby the chattering effect is avoided. By using tools from graph theory and stability analysis of dynamical systems, it is proven that asymptotical output consensus can be achieved if the underlying network topology contains a directed spanning tree rooted at the leader and the control parameters are suitably chosen. Finally, a numerical simulation is presented to verify the theoretical result.

In this paper, we study the broadcast problem in wireless networks when the broadcast is helped by a labelling scheme. We focus on two variants of broadcast: broadcast without acknowledgment (i.e. the initiator of the broadcast is not notified at the end of broadcast) and broadcast with acknowledgment. Our contribution is threefold. First, we improve in terms of memory complexity a recent [12] labelling-based broadcast scheme with acknowledgment designed for arbitrary networks. Second, we propose label optimal broadcast algorithms in level separable networks (a class of networks issued from recent studies in Wireless Body Area Networks). In this class of networks we propose an acknowledgment-free broadcast strategy using 1-bit labels and broadcast with acknowledgment using 2-bits labels. In the class of level-separable networks, our algorithms finish within 2D rounds, where D is the eccentricity of the broadcast initiator. Interestingly, the time complexity of broadcast in the case of level-separable networks does not depend on the size of the network but rather on the initiator eccentricity which makes this class of graphs interesting for further investigation. Finally, we study the hardness of determining that a graph is level separable. Our study shows that even though checking that a separation is a level separation can be done in polynomial time, determining that a graph has the level separable property is NP-complete. This result opens interesting independent research directions.KeywordsLabelling schemeBroadcastWireless networks

Neighbor discovery is a critical first step in establishing communication in a wireless ad-hoc network. Existing quorum-based neighbor discovery algorithms only consider a pair of nodes and ensure that this pair can communicate at least once in a bounded interval. However, when the node density of a wireless network increases, collisions are more likely to happen, which makes these quorum-based algorithms inefficient in practice. We propose a novel self-adapting quorum-based neighbor discovery algorithm that can dynamically adjust its cycle pattern to decrease the impact of such collisions. We first assess the collision problem in wireless networks when using quorum-based neighbor discovery algorithms and then establish a theoretical framework to analyze the discovery delay when considering collision effects. Guided by these theoretical results, we design a self-adapting mechanism for cycle patterns in quorum-based algorithms. Simulation results show that our algorithm can achieve complete neighbor discovery in less time than existing quorum-based neighbor discovery algorithms.

Optimization is one of the best alternative solutions for addressing majority of the computational challenges associated with the wireless sensor network (WSN). At present, the successful implications of bio-inspired approaches are significantly proven to solve diversified complex problems in wireless network. However, after reviewing the existing literatures, it was found that yet there is bigger scope to enhance the capability of bio-inspired approach in the area of WSN. Therefore, this paper introduces a novel bio-inspired algorithm called as killer whale hunting (KWH) targeted for optimizing the data aggregation process with highly improved network sustenance capability. The formulation of the algorithm is designed on the basis of social and cognitive behaviour of killer whale which has a distinct style of hunting its prey. Using analytical modelling, the proposed approach was found to offer better energy efficiency and sufficient data forwarding capability in contrast to existing energy-efficient bio-inspired techniques.

Under given energy constraints, a fundamental problem in wireless networks is to maximize network lifetime and prolong network operational lifetime. Since nodes in the network can be affected with interference of peripheral nodes, it causes collisions and congestions. Thus, whole network consumes more energy. It is clear that the higher density of network the higher degree of nodes. It leads to more redundant coverage, i.e. more overlapped areas (joint areas between adjusted nodes) in the network, which also increases energy consumption and probability of collisions. This paper proposes an energy-efficient topology control algorithm. Based on location awareness, the proposed algorithm minimizes a set of the relay nodes keeping the connectivity and whole network coverage. To address this, the algorithm calculates density of network and divides the transmission range of a node into border area and core area. Then, the algorithm calculates overlapped areas between border nodes and selects relays amongst them. As a result, the network can be seen as a sparse network in which the overlapped areas are reduced. Since only selected nodes act as relays at the particular time interval, it helps to reduce whole network energy consumption, prolong operational network lifetime and reduce collisions or congestions. The results of simulation show that the proposed algorithm improves energy-efficiency of the network while preserving connectivity and functions of routing agent.

Bipartite event-triggered impulsive output consensus for switching multi-agent systems with dynamic leader

Distributed consensus of heterogeneous multi-agent systems subject to switching topologies and delays

무선 네트워크에서 최소 에너지 브로드캐스트 문제는 네트워크에 배치된 모든 노드가 브로드캐스팅과정에서 데이터 전송에 사용되는 에너지를 최소화하는 문제이다. 본 논문은 무선 센서 네트워크에서 최소 에너지 브로드캐스트 문제를 효과적으로 해결할 수 있는 메타휴리스틱 기법인 타부서치 알고리즘을 제안한다. 보다 효과적인 해 검색을 위해 제안된 알고리즘은 새로운 이웃해 생성방식과 복구함수를 적용한다. 제안된 알고리즘의 성능평가는 배치된 모든 노드로의 브로드캐스팅 시 전송 에너지와 알고리즘 실행시간 관점에서 기존의 알고리즘과 비교를 하였으며, 실험 결과에서 제안된 알고리즘이 최소 에너지 브로드캐스트 문제에 효과적으로 적용됨을 보여준다. The minimum energy broadcast problem is for all deployed nodes to minimize a total transmission energy for performing a broadcast operation in wireless networks. In this paper, we propose a Tabu search algorithm to solve efficiently the minimum energy broadcast problem on the basis of meta-heuristic approach in wireless sensor networks. In order to make a search more efficient, we propose a novel neighborhood generating method and a repair function of the proposed algorithm. We compare the performance of the proposed algorithm with other existing algorithms through some experiments in terms of the total transmission energy of nodes and algorithm computation time. Experimental results show that the proposed algorithm is efficient for the minimum energy broadcast problem in wireless sensor networks.

This paper studies joint scheduling and network coding in wireless multicast networks with independent sources. Designing a network coding solution for wireless networks involves scheduling interference-free transmissions and optimizing a performance measure for the predetermined scheduling sets, followed by constructing network codes for the specific solution. In such a design process, the results of prior steps need to provide enough information to the subsequent steps. In this paper, we formulate a linear optimization problem whose results can be used to design a coding solution. We build our work on previous works and present statistics that show the importance of incorporating unequal timeshares in designing network codes. In particular, our statistics show a throughput improvement of about 35% in maximum flow problems and energy savings between 13% and 30%, depending on the network size, in minimum energy problems. We also present the requirements of code construction algorithms for wireless networks that capture the broadcast property of these networks and can design proper codes when timeshares are unequal. In particular, the adaptation of a centralized network coding scheme for wireless networks is discussed. Overall, the work reported here provides a three-step solution to derive network codes that optimize a performance criterion of interest while also solving the scheduling problem in multihop wireless networks.