Information searches are the most common application within social networks. Normally, the social network is modeled as a network graph, consisting of nodes (In the rest of the paper, unless otherwise specified, we will use the terms “user” and “node” interchangeably.) representing users within the network and edges representing relationships between users. Choosing the appropriate nodes to form an auxiliary structure for supporting the effective query message spreading can reduce the troublesome repeated queries. To accomplish this, a hybrid search (HS) scheme is proposed. If the query message is received by a node belonging the auxiliary structure constructed by dynamic weighted distributed label clustering (DW-DLC), it would be flooded to all neighbors of the visited node; otherwise, it would be forwarded to one neighbor of the visited node. The DW-DLC based auxiliary structure can accelerate the process of obtaining required information within the network. The simulation results show that the HS+DW-DLC scheme can reduce the average searching delay time, even in a required-information-scarce social network. In addition, the proposed scheme can generate a relatively low amount of repeated messages to lower repeatedly asking social network users.

Information searching is the most common application in the social network. Choosing appropriate users as the clusterheads in a clustering based social network can facilitate to effectively spread query messages, resulting in efficient searching performance. To do so, we propose a hybrid searching (HS) scheme and use the dynamic weighted distributed label clustering (DW-DLC) structure to assist the searching process. The DW-DLC structure can accelerate the process of finding target information in the social network. The simulation results depict that the HS+DW-DLC scheme can reduce the average searching delay time by more than 90% even in a information-scarce social network which only 8% of total nodes can provide the target information. Meanwhile, HS+DW-DLC can generate a lowest average message overhead, which may burden the network, compared to other schemes.

This paper proposes a new algorithm, TBRA (Termites- Based Routing Algorithm), for use in three- dimensional mobile wireless sensor networks. The TBRA is a routing selection strategy based on the concept of the ant colony optimization algorithm. It is difficult to establish and maintain optimal routes in a 3D space because the RSSI, energy of sensor nodes, vary with time. This routing selection strategy can be used for various traffic conditions by measuring and counting the average energy of nodes, RSSI value. The main contribution of this study combines ACO algorithm and Durkin's propagation model to derive an efficient routing scheme for wireless sensor networks in a 3D space.