InformationCentric Local Resource Sharing System on Smart Phones DevicetoDevice (D2D) communication is considered as an efficient approach to improve current wireless networks. However, for intergroup communication, since devices are using the same IP address segment, IP conflicts can be induced into D2D networks. To address this problem, we propose an InformationCentric resource sharing system for D2D communication network. In the system, both P2P and WLAN network adaptor interfaces are adopted simultaneously for establishing a D2D network. A socket reusing mechanism is proposed for intergroup communication. In addition, to improve content distribution and retrieval, we base our system on InformationCentric networking (ICN) paradigm. We design ICN flow tables on network nodes to realize request forwarding and data backtracking. To demonstrate the feasibility and effectiveness, we have implemented the system on commercial Android devices using WiFi Direct technology. Experimental results show that the proposed InformationCentric resource sharing system is feasible for D2D network in terms of data transmission and energy consumption. The average latency for transmitting 1MB data is 257.23ms; i.e., the throughput is up to 31.1 Mbps. The average energy consumption for transmitting 100MB data is only about 0.66 mAh.

A novel collision aware network assisted device discovery scheme empowering massive D2D communications in 3GPP LTEA networks Abstract   With the proliferation of proximity based servicesapplications, DevicetoDevice (D2D) communication has become an emerging technology in facilitating data transfer among proximal cellular User Equipments (UEs). However one of the most challenging issues in D2D communication is the need for a robust device discovery scheme that effectively discovers UEs without any performance bottlenecks. In a densely populated cellular network, the conventional device discovery schemes proposed in the literature suffer from one or more adversities. High signaling overhead, large number of collisions and inefficient use of resources are some of the major issues that severely limit the performance of a device discovery scheme. Based on the characteristics of the networkassisted and autonomous device discovery schemes, we propose a novel device discovery scheme that discovers proximal UEs without causing any significant performance degradation. The cellular UEs are first divided into clusters based on their social relationship status and common interests. Every cluster will then execute a device discovery algorithm which is composed of two stages. In the first stage, UEs discover their neighbors using the conventional beacon based discovery scheme. The second stage comprises of successful UEs reporting to BS by initiating the LTE random access procedure. In this way, we not only reduce the signaling overhead but also enable substantial number of device discoveries to happen simultaneously at any instant of time. Further, we present a stochastic geometry based framework to analyze the collision probability and link discovery probability of the proposed scheme. Through extensive simulations we find that our proposed device discovery scheme effectively results in higher discovery probability compared to a recently proposed discovery scheme, by reducing the amount of collisions.