The wireless sensor networks (WSNs) are characterized by several small nodes able to perform measurements on one or more parameters and to communicate with each other through several protocols. Most of home automation...
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The wireless sensor networks (WSNs) are characterized by several small nodes able to perform measurements on one or more parameters and to communicate with each other through several protocols. Most of home automation networks (depending on the specific application) are mainly characterized by periodic traffic flows. In soft real-time contexts, the main problem is represented by the efficient allocation of guaranteed time slots (GTSs) for periodic traffic flows transmission in IEEE 802.15.4 networks. Moreover, it is important to ensure adequate performance for those embedded devices competing for the access to the medium through the carrier sense multiple access/collision avoidance algorithm (CSMA/CA). The main aim of this paper is to show a new approach for network flows scheduling in home automation applications based on IEEE 802.15.4 wireless sensor networks. This work addresses several advantages due to the introduction of rate monotonic (RM) for guaranteed time slots (GTSs) allocation combined with priority-based CSMA/CA for latencies reduction on transmission attempts as clearly demonstrated by obtained results.
Existing technologies are inapplicable to localization in constrained space, especially when considering environmental factors. These methods with low localization accuracy cannot meet the location requirements in con...
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Existing technologies are inapplicable to localization in constrained space, especially when considering environmental factors. These methods with low localization accuracy cannot meet the location requirements in constrained space, for they usually call for lots of computation time and process resources. Moreover, they are easily interfered by environmental factors and attacks from other users. Consequently, in order to improve location accuracy in constrained space, an asymmetric event-driven localization algorithm (AELA) is proposed in this paper, which is based on the combination of event distribution and anchor node achieving a distributed location estimation strategy, so that it can satisfy the localization requirement of constrained space and achieve the high-accuracy localization with a small amount of events and anchor nodes. Meanwhile, to improve the accuracy of the algorithm, a set of candidate events are adopted to prune the event which does not meet location accuracy requirements. We finally perform experiments in indoor corridors, and the results show that the proposed algorithm has higher performances not only on localization accuracy and energy consumption but also on anti-interference ability than RSSI and MSP.
WirelessHART is an emerging wireless sensor network protocol. In this paper, a joint graph routing algorithm for maximizing the network lifetime (JRMNL) in WirelessHART is proposed. Node communication load factor is a...
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WirelessHART is an emerging wireless sensor network protocol. In this paper, a joint graph routing algorithm for maximizing the network lifetime (JRMNL) in WirelessHART is proposed. Node communication load factor is approximately estimated by matrix operations for the first time. Then node communication load, the residual energy, and the link transmission power are integrated as a link cost function that is accurately measured in this algorithm. A node chooses the optimal next hop by comparing the link cost function of all its neighbor nodes, which guarantees the energy balancing of the whole network. Simulation results show that the proposed algorithm can extend network lifetime by a factor of 2 relative to the maximum residual energy selection algorithm and prolong the network lifetime by a factor of 7 relative to the minimum transmission power routing algorithm, but the average energy consumption per route will increase by 2 dBm compared with the minimum transmission power routing algorithm.
In wireless networks, wireless sniffers are distributed in a region to monitor the activities of users. It can be applied for fault diagnosis, resource management, and critical path analysis. Due to hardware limitatio...
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In wireless networks, wireless sniffers are distributed in a region to monitor the activities of users. It can be applied for fault diagnosis, resource management, and critical path analysis. Due to hardware limitations, wireless sniffers typically can only collect information on one channel at a time. Therefore, it is a key topic to optimize the channel selection for sniffers to maximize the information collected, so as to maximize the Quality of Monitoring (QoM) for wireless networks. In this paper, a Multiple-Quantum-Immune-Clone-Algorithm- (MQICA-) based solution was proposed to achieve the optimal channel allocation. The extensive simulations demonstrate that MQICA outperforms the related algorithms evidently with higher monitoring quality, lower computation complexity, and faster convergence. The practical experiment also shows the feasibility of this algorithm.
In dynamic wireless ad hoc networks (DynWANs), autonomous computing devices set up a network for the communication needs of the moment. These networks require the implementation of a medium access control (MAC) layer....
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In dynamic wireless ad hoc networks (DynWANs), autonomous computing devices set up a network for the communication needs of the moment. These networks require the implementation of a medium access control (MAC) layer. We consider MAC protocols for DynWANs that need to be autonomous and robust as well as have high bandwidth utilization, high predictability degree of bandwidth allocation, and low communication delay in the presence of frequent topological changes to the communication network. Recent studies have shown that existing implementations cannot guarantee the necessary satisfaction of these timing requirements. We propose a self-stabilizing MAC algorithm for DynWANs that guarantees a short convergence period, and by that, it can facilitate the satisfaction of severe timing requirements, such as the above. Besides the contribution in the algorithmic front of research, we expect that our proposal can enable quicker adoption by practitioners and faster deployment of DynWANs that are subject changes in the network topology.
Distributed coordination is critical for a multirobot system in collective cleanup task under a dynamic environment. In traditional methods, robots easily drop into premature convergence. In this paper, we propose a S...
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Distributed coordination is critical for a multirobot system in collective cleanup task under a dynamic environment. In traditional methods, robots easily drop into premature convergence. In this paper, we propose a Swarm Intelligence based algorithm to reduce the expectation time for searching targets and removing. We modify the traditional PSO algorithm with a random factor to tackle premature convergence problem, and it can achieve a significant improvement in multi-robot system. It performs well even in a obstacle environment. The proposed method has been implemented on self-developed simulator for searching task. The simulation results demonstrate the feasibility, robustness, and scalability of our proposed method compared to previous methods.
In wireless distributed sensor networks, one open problem is how to guarantee the reliable relay selection based on the quality of services diversity. To address this problem, we focus on the reliable adaptive relay s...
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In wireless distributed sensor networks, one open problem is how to guarantee the reliable relay selection based on the quality of services diversity. To address this problem, we focus on the reliable adaptive relay selection approach and adaptive QoS supported algorithm, based on which we present a Markov chain model, in consideration of different packet states and error control algorithm assignment. The mathematical analyses and NS-2 simulation results show that the proposed relay selection approach could perform better in terms of saturation throughput, reliability, and energy efficiency, compared with the traditional approaches. More importantly, the quality of real-time multimedia streaming is improved significantly, in terms of decodable frame ratio and delay.
作者：
Liu, DongJinan Univ
Dept Comp Sci Guangzhou 510632 Guangdong Peoples R China
Real-time Online Interactive Application (ROIA) is an emerging distributed application recently. ROIA needs a highly robust and efficient architecture to cope with the huge concurrent users. Previous works are almost ...
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Real-time Online Interactive Application (ROIA) is an emerging distributed application recently. ROIA needs a highly robust and efficient architecture to cope with the huge concurrent users. Previous works are almost based on the C/S or P2P mode, and their scalability and resource utilization are relatively low. So we try to take advantage of the cloud computing technologies to achieve higher scalability and resource utilization. However, as ROIA servers focused on several data centers in cloud computing rather than being scattered in many areas, it will increase in part users' network delays and affect their user experiences in ROIA. To cope with this problem, we propose an improved Dead Reckoning (DR) algorithm. Traditional DR algorithm is mostly based on the classic formula of physics to predict, without taking the influence of the user's target under the different situations into account, so there are some limitations. This paper proposes an improved DR algorithm based on target-extrapolating in a cloud platform for ROIA, elaborates the basic idea of the improved algorithm and the computational model formula, and then carries out a simulation experiment. The analyses of the simulation results show that the improved algorithm is superior to traditional one.
Node location is of great significance as a supporting technology of wireless sensor network (WSN). The information without position would be greatly devalued. So this paper is about location algorithm for nodes of sh...
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Node location is of great significance as a supporting technology of wireless sensor network (WSN). The information without position would be greatly devalued. So this paper is about location algorithm for nodes of ship-borne WSN based on research on structure of ship and work environment of ship-borne WSN. The whole location process consists of two steps: one is location algorithm among cabins (LAAC), and the other one is location algorithm in the cabin (LAIC). LAAC refers to location with the topology of ship-borne WSN. We can learn which cabin the node lies in. LAIC refers to location based on received signal strength indication (RSSI), we can get distance relationship between nodes by RSSI, and then obtain the specific location by solving this distance relationship. In the last part, this paper verifies the designed location algorithm by experimenting on "A" ship. Experiments show that the location algorithm designed by this paper is feasible.
This paper presents a novel data validation algorithm for wireless sensor network. We applied qualitative methods such as heuristic rule, temporal correlation, spatial correlation, Chauvenet's criterion, and modif...
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This paper presents a novel data validation algorithm for wireless sensor network. We applied qualitative methods such as heuristic rule, temporal correlation, spatial correlation, Chauvenet's criterion, and modified z-score as algorithms for validating sensor data samples for faults. Performance of the algorithms is evaluated using real data samples of WSNs prototype for environment monitoring injected with different types of data faults such as out-of-range faults, struck-at faults, and outliers and spike faults. Results show heuristic rule, temporal correlation, spatial correlation, chauvenet's criterion, and modified z-score method sit at different point on accuracy, no single method is perfect in detecting different types of data faults and reports false positives when sensor data samples contain different types of data faults. Selected effective methods such as heuristic rule, temporal correlation, and modified z-score are applied successively to data set for detecting different types of data faults but report false positives due to masking effects and increased fault rate. Finally we propose a novel data validation algorithm that uses novel approach in applying heuristic rule, temporal correlation, and modified z-score to data set for detecting different types of data faults. Compared to other methods, the proposed novel data validation algorithm is effective in detecting different types of data faults and reports high fault detection rate by eliminating false positives.
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