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APTEEN is a typical routing protocol for wireless sensor networks, but when clustering, cluster heads are randomly selected, which makes it easy to select nodes with low residual energy as cluster heads, thus forming network holes. At the same time, in multi hop transmission, the cluster head near the sink node is overloaded due to forwarding a large amount of data. Aiming at these problems, this paper introduces PSO algorithm and proposes ADCH-EPE-APTEEN routing protocol. In order to make the particle swarm optimization algorithm more suitable for routing protocol, this paper first proposes DCA-PSO based on particle swarm optimization algorithm. DCA-PSO uses the classification adaptive change inertia weight for different states of particles in the optimization process. At the same time, dynamic learning factor is used to improve the influence of particle experience and other particle experience on convergence speed and to improve the optimization accuracy and speed of the algorithm. Secondly, when APTEEN routing protocol is networked, the cluster head is selected by DCA-PSO, in which the residual energy of nodes, the location of nodes, and the energy distribution around nodes are fully taken into consideration. Thirdly, considering the distance between nodes and the sink node, the residual energy and the energy distribution around nodes, a front area is set up in the cluster located in the upper half and the assistant cluster head is selected in the front area through the DCA-PSO algorithm. The simulation results show that the DCA-PSO algorithm can significantly improve the search speed and precision compared with the PSO algorithm. Compared with APTEEN routing protocol, the ADCH-EPE-APTEEN routing protocol can reduce the network energy consumption rate and extend network lifetime by 173%. [ABSTRACT FROM AUTHOR]

In this paper, the time triggered hybrid scheduler (TTH) is implemented in the distributed real time embedded systems along with the operation of dynamic frequency scaling (DFS) since it overcomes the problem of time triggered cooperative scheduler (TTC) for distributed systems and also the decreases the power consumption. This scheduler is implemented along with the token ring network protocol for the communication scheduling. In hard real time systems, ideally, no deadline may ever be missed and hence the co-operative and pre-emptive are combined in this paper to achieve optimum efficiency. DFS is used to provide robustness to the network and also reduces the power utilization. This TTH scheduler is more advantageous than TTC scheduler in distributed system, since long task problem can be overcome by means of this algorithm. The model is simulated using the TORSCHE toolbox of the MATLAB. Some of the applications of this scheduling are data acquisition and sampling in wireless sensor networks, control system engineering, patient monitoring using wireless sensor networking and so on. [ABSTRACT FROM AUTHOR]

This paper presents a radial cluster heads selection mechanism for homogenous wireless sensor networks. It aims to ensure a good load balancing and enhance the network lifetime. A performance comparison between LEACH, Mod_LEACH, Multi-Chain-PEGASIS, M-GEAR protocols and our proposal in term of network lifetime, stability/instability periods and the evolution of the number of cluster heads is carried out in this work. Obtained results show that developing an efficient cluster heads selection algorithm enhances considerably the network lifetime and the QoS in the network. Simulations results under NS3 simulator showed that our proposal can extend the network life more than 300% compared to the famous LEACH protocol and ensure a network lifetime of about 5000 rounds while it does not exceed 2500 rounds using M-GEAR. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSN) with the Internet of Things (IoT) play a vital key concept while performing the information transmission process. The WSN with IoT has been effectively utilized in different research contents such as network protocol selection, topology control, node deployment, location technology and network security, etc. Among that, node location is one of the crucial problems that need to be resolved to improve communication. The node location is directly influencing the network performance, lifetime and data sense. Therefore, this paper introduces the Bird Swarm Optimized Quasi-Affine Evolutionary Algorithm (BSOQAEA) to fix the node location problem in sensor networks. The proposed algorithm analyzes the node location, and incorporates the dynamic shrinking space process is to save time. The introduced evolutionary algorithm optimizes the node centroid location performed according to the received signal strength indications (RSSI). The created efficiency in the system is determined using high node location accuracy, minimum distance error, and location error. [ABSTRACT FROM AUTHOR]

Quality of Service (QoS) assurance in Wireless Sensor Network (WSN) is a tough task, and it is more exciting due to the scarcity of resources. The requirement of different WSN applications running over has different constraints. In QoS, routing protocol the network has to balance the traffic. This paper presents a novel heuristic routing algorithm known as QoS assured Multi-objective Hybrid Routing Algorithm (Q-MOHRA) for Heterogeneous WSN. Q-MOHRA takes into account the link (energy, hop count, link quality indicator etc.) and path (jitter) metrics for optimal path selection. The performance of Q-MOHRA is evaluated through intensive simulation and equated with Simple Hybrid Routing Protocol (SHRP) and Dynamic Multi-objective Routing Algorithm (DyMORA). The metrics such as average energy consumption, residual energy, packet delivery ratio, jitter, and normalized routing load are used for comparison. The performance of Q-MOHRA has been observed to outclass SHRP and DyMORA. It improves the packet delivery ratio by 24.31% as compared to SHRP and 11.86% as compared to DyMORA. Q-MOHRA outperforms DyMORA in terms of average energy consumption by a factor of 8.27%. [ABSTRACT FROM AUTHOR]

Abstract   Timeliness guarantee is an important feature of the recently standardized IEEE 802.15.4 protocol, turning it quite appealing for Wireless Sensor Network (WSN) applications under timing constraints. When operating in beacon-enabled mode, this protocol allows nodes with real-time requirements to allocate Guaranteed Time Slots (GTS) in the contention-free period. The protocol natively supports explicit GTS allocation, i.e. a node allocates a number of time slots in each superframe for exclusive use. The limitation of this explicit GTS allocation is that GTS resources may quickly disappear, since a maximum of seven GTSs can be allocated in each superframe, preventing other nodes to benefit from guaranteed service. Moreover, the GTS may be underutilized, resulting in wasted bandwidth. To overcome these limitations, this paper proposes i-GAME, an implicit GTS Allocation Mechanism in beacon-enabled IEEE 802.15.4 networks. The allocation is based on implicit GTS allocation requests, taking into account the traffic specifications and the delay requirements of the flows. The i-GAME approach enables the use of one GTS by multiple nodes, still guaranteeing that all their (delay, bandwidth) requirements are satisfied. For that purpose, we propose an admission control algorithm that enables to decide whether to accept a new GTS allocation request or not, based not only on the remaining time slots, but also on the traffic specifications of the flows, their delay requirements and the available bandwidth resources. We show that our approach improves the bandwidth utilization as compared to the native explicit allocation mechanism defined in the IEEE 802.15.4 standard. We also present some practical considerations for the implementation of i-GAME, ensuring backward compatibility with the IEEE 801.5.4 standard with only minor add-ons. Finally, an experimental evaluation on a real system that validates our theoretical analysis and demonstrates the implementation of i-GAME is also presented. [ABSTRACT FROM AUTHOR]

Complex Events are sequences of sensor measurements indicating interesting or unusual activity in the monitored process. Such events are ubiquitous in a wide range of Wireless Sensor Network (WSN) applications, yet there does not exist a common mechanism that addresses both the considerable constraints of WSNs and the specific properties of Complex Events. We argue that Complex Events cannot be described using standard threshold-based or composite logic approaches and attempting to represent them as such can lead to unpredictable execution cost while detection accuracy suffers from erroneous recording of observations which are common in WSNs. To address this, we develop a family of Complex Event Detection (CED) algorithms based on online symbolic conversion of sensor readings. With fixed execution cost and modest resource requirements, the CED algorithms cater for exact, approximate, non-parametric, multiple and probabilistic detection that is neither application nor data dependent. Overall, full implementation and simulations provide experimental evidence of the advantages of the proposed approach. We find that the proposed algorithms minimise configuration, promote unattended operation and complement the goal of prolonged lifetime-factors that satisfy the long-term research vision predicting Internet-scale WSNs comprising billions of devices. [ABSTRACT FROM AUTHOR]

The problem of collaborative tracking of mobile nodes in wireless sensor networks is addressed. By using a novel metric derived from the energy model in LEACH (W.B. Heinzelman, A.P. Chandrakasan and H. Balakrishnan, Energy-Efficient Communication Protocol for Wireless Microsensor Networks, in: Proceedings of the 33rd Hawaii International Conference on System Sciences (HICSS '00), 2000) and aiming at an efficient resource solution, the approach adopts a strategy of combining target tracking with node selection procedures in order to select informative sensors to minimize the energy consumption of the tracking task. We layout a cluster-based architecture to address the limitations in computational power, battery capacity and communication capacities of the sensor devices. The computation of the posterior Cramer-Rao bound (PCRB) based on received signal strength measurements has been considered. To track mobile nodes two particle filters are used: the bootstrap particle filter and the unscented particle filter, both in the centralized and in the distributed manner. Their performances are compared with the theoretical lower bound PCRB. To save energy, a node selection procedure based on greedy algorithms is proposed. The node selection problem is formulated as a cross-layer optimization problem and it is solved using greedy algorithms. [ABSTRACT FROM AUTHOR]

Clustering provides an effective method for prolonging the lifetime of a wireless sensor network. Current clustering algorithms usually utilize two techniques; selecting cluster heads with more residual energy, and rotating cluster heads periodically to distribute the energy consumption among nodes in each cluster and extend the network lifetime. However, they rarely consider the hot spot problem in multihop sensor networks. When cluster heads cooperate with each other to forward their data to the base station, the cluster heads closer to the base station are burdened with heavier relay traffic and tend to die much faster, leaving areas of the network uncovered and causing network partitions. To mitigate the hot spot problem, we propose an Unequal Cluster-based Routing (UCR) protocol. It groups the nodes into clusters of unequal sizes. Cluster heads closer to the base station have smaller cluster sizes than those farther from the base station, thus they can preserve some energy for the inter-cluster data forwarding. A greedy geographic and energy-aware routing protocol is designed for the inter-cluster communication, which considers the tradeoff between the energy cost of relay paths and the residual energy of relay nodes. Simulation results show that UCR mitigates the hot spot problem and achieves an obvious improvement on the network lifetime. [ABSTRACT FROM AUTHOR]