# SIoT: A New Strategy to Improve the Network Lifetime with an Efficient Search Process
## 1 Introduction
* **Social Object Relationship (SOR):** It is established if there is a liaison between the objects. In SIoT every node will be able to search for the desired service using its friends. As a node can be surrounded by many nodes, selecting a set of friends from the neighboring nodes is an essential phase, which affects the service search task. The efficiency of Friendship selection strategies is often measured in terms of the parameters of network navigability: giant component, average path length, average local clustering coefficient, average degree, and diameter of the network. The enhancement of these parameters boosts rapid search for the service but does not guarantee it. Furthermore, each node must manage the selected friends, such that the selection of many friends affects negatively the capacity of storage, battery power, etc. So, it is desirable to limit the number of friendships for each node. On another side, during the service search, the nodes lose their energy which leads to reduce network lifetime; therefore, the customer nodes can be unable to obtain the requested services. The research question is how to create efficient strategies that improve the parameters of network navigability and increase the network lifetime, also to propose a new mechanism to speed up more the service search process. The objective is to create a new approach for the fastest, dynamic, and autonomous service search among nodes in SIoT by considering the capacities of different devices in SIoT. Furthermore, the current work can provide many benefits for practitioners and researchers who want to develop or integrate IoT applications that can exploit the services provided by the systems of smart healthcare, smart agriculture, smart city, etc. Moreover, it is designed to support the 5 th generation (5G) that is required to quickly and efficiently respond to complex IoT requests. To overcome the limitations associated with SIoT, we propose a new approach with features described as follows. * Firstly, we create the node groups, where each group has only one master node, and these groups run a consensus algorithm to agree on a specific value. * Secondly, we create a new friendship selection strategy using groups of nodes based on an agreed value and other properties. The social network is built to achieve a better navigability and to be a suitable network for minimizing the number of hops and balancing the resources. * Thirdly, a node sorts and resorts all the friendships based on the capabilities of nodes, groups, their centrality, and popularity, in order to speed up the search task and increase the network lifetime. The performance of our contribution has been analyzed in terms of giant component, average degree, average local clustering coefficient, average path length, network diameter, number of hops to achieve the providers, and network lifetime. The remainder of this paper is organized as follows: Section 2 introduces the related works, Section 3 includes the problem definition and parameters of a network, Section 4 presents our proposed contribution, Section 5 gives simulation results and discussion, and the final section concludes the paper.