Hierarchical routing algorithm is now a hotspot in the field of wireless sensor network. Aiming at the problem that the energy of sensor nodes are limited, a hierarchical routing algorithm for wireless sensor networks based on small world model (HASWNM) was proposed. The Wireless Sensor Network (WSN) could reflect characteristics of the small world by adding nodes with high performance as well as shortcuts among cluster heads. As the energy consumption was mainly concentrated in the data transmission phase, the energy of the cluster head was taken into account while choosing the relay node between clusters. Besides, the different adaptive search area was determined according to the distance between the cluster head and the base station. The experimental results showed that the network can show the characteristics of small world when the number of high-performance nodes reached 100, and compared to the algorithms of CSWN (topology Control based on Small World Network), TSWN (Tree-based Small World Network), DASM (Directed Angulation towards the Sink node Model), the number of death rounds of the first node was delayed by 6%,6%,29% separately, and the average energy consumption of the network per round was reduced by 5%,12%,17% respectively. Thus the wireless sensor network constructed by the proposed algorithm has the characteristics of small world and low energy consumption.

In order to solve the problems of high outage probability and unbalanced load in dense small cellular networks, an energy-efficient scheme based on load balancing was proposed. The network energy-efficiency was maximized through joint optimization of load balancing and base station on/off control strategy under the constraints of guaranteed user outage probability and minimum rate. The optimization problem is a non-convex Non-deterministic Polynomial-hard (NP-hard) problem, and it is quite complex to obtain the optimal solution. Therefore, the original optimal problem was decomposed into two suboptimal subproblems. Firstly, the optimal load balancing strategy with the given base station on/off control strategy was given by the proposed load balancing scheme. Secondly, the optimal base station on/off control strategy was designed under the constraint of satisfying the minimum user rate. The experimental results show that, when the number of users is less than 180, the outage probability of the proposed scheme is zero while the outage probability of the traditional Maximum Signal to Interference plus Noise Ratio (Max-SINR) algorithm reaches 11%. The network energy-efficiency of the proposed scheme is higher than those of the base station Randomly-off (Ran-off) algorithm and the base station Not-off (No-off) algorithm. The proposed scheme can improve network energy-efficiency and ensure load balance.