Wireless sensor networks usually deploy sensor nodes with limited energy resources in unattended environments so that people have difficulty in replacing or recharging the depleted devices. In order to balance the energy dissipation and prolong the network lifetime, this paper proposes a routing spanning tree-based clustering algorithm (RSTCA) which uses routing spanning tree to analyze clustering. In this study, the proposed scheme consists of three phases: setup phase, cluster head (CH) selection phase and steady phase. In the setup phase, several clusters are formed by adopting the K-means algorithm to balance network load on the basis of geographic location, which solves the randomness problem in traditional distributed clustering algorithm. Meanwhile, a conditional inter-cluster data traffic routing strategy is created to simplify the networks into subsystems. For the CH selection phase, a novel CH selection method, where CH is selected by a probability based on the residual energy of each node and its estimated next-time energy consumption as a function of distance, is formulated for optimizing the energy dissipation among the nodes in the same cluster. In the steady phase, an effective modification that counters the boundary node problem by adjusting the data traffic routing is designed. Additionally, by the simulation, the construction procedure of routing spanning tree (RST) and the effect of the three phases are presented. Finally, a comparison is made between the RSTCA and the current distributed clustering protocols such as LEACH and LEACH-DT. The results show that RSTCA outperforms other protocols in terms of network lifetime, energy dissipation and coverage ratio.

This paper proposes two algorithms to balance energy consumption among sensor nodes by distributing the workload of image compression tasks within a cluster on wireless sensor networks. The main point of the proposed algorithms is to adopt the energy threshold, which is used when we implement the exchange and/or assignment of tasks among sensor nodes. The threshold is well adaptive to the residual energy of sensor nodes, input image, compressed output, and network parameters. We apply the lapped transform technique, an extended version of the discrete cosine transform, and run length encoding before Lempel-Ziv-Welch coding to the proposed algorithms to improve both quality and compression rate in image compression scheme. We extensively conduct computational experiments to verify the our methods and find that the proposed algorithms achieve not only balancing the total energy consumption among sensor nodes and, thus, increasing the overall network lifetime, but also reducing block noise in image compression.

This paper presents a new routing approach to extend the effective lifetime of mobile ad hoc networks (MANET) considering both residual battery energy of the participating nodes and routing cost. As the nodes in ad hoc networks are limited in power, a power failure occurs if a node has insufficient remaining energy to send, receive or forward a message. So, it is important to minimize the energy expenditure as well as to balance the remaining battery power among the nodes. Cost effective routing algorithms attempt to minimize the total power needed to transmit a packet which causes a large number of nodes to loose energy quickly and die. On the other hand, lifetime prediction based routing algorithms try to balance the remaining energies among the nodes in the networks and ignore the transmission cost. These approaches extend the lifetime of first few individual nodes. But as nodes spend more energy for packet transfer, power failures occurs within short interval resulting more number of total dead node earlier. This reduces the effective lifetime of the network, as at this stage successful communication is not possible due to the lack of forwarding node. The proposed method keeps the transmission power in modest range and at the same time tries to reduce the variance of the residual energy of the nodes more effectively to obtain the highest useful lifetime of the networks in the long run. Nonetheless, movement of nodes frequently creates network topology changes via link breaks and link creation and thus effects on the stability of the network. So, the pattern of the node movement is also incorporated in our route selection procedure.

Ubiquitous sensor networks (USNs) are comprised of energy constrained nodes. This limitation has led to the crucial need for energy-aware protocols to produce an efficient network. We propose a sleep scheduling scheme for balancing energy consumption rates in a single hop cluster based network using Analytical Hierarchy Process (AHP). We consider three factors contributing to the optimal nodes scheduling decision and they are the distance to cluster head (CH), residual energy, and sensing coverage overlapping, respectively. We also propose an integrated sleep scheduling and geographical multi-path routing scheme for USNs by AHP. The sleep scheduling is redesigned to adapt the multi-hop case. For the proposed routing protocol, the distance to the destination location, remaining battery capacity, and queue size of candidate sensor nodes in the local communication range are taken into consideration for next hop relay node selection. The proposed schemes are observed to improve network lifetime and conserve energy without compromising desired coverage. In the multi-hop case, it can further reduce the packet loss rate and link failure rate since the buffer capacity is considered.

The energy conservation law and the optical theorem in the grating theory are discussed: the energy conservation law states that the incident energy is equal to the sum of diffracted energies and the optical theorem means that the diffraction takes place at the loss of the specularly reflection amplitude. A mathematical relation between the optical theorem and the energy conservation law is given. Some numerical examples are given for a TM plane wave diffraction by a sinusoidal surface.

Low luminous efficacy is one of the major drawbacks of PDPs, with the discharge being the predominant limiting factor. Numeric simulations granting deeper insight in the core processes of the discharge are presented and the key parameters influencing the plasma efficiency are examined.