Cooperative caching game based on social trust for D2D communication networks

Abstract

Content sharing via device-to-device (D2D) communications has become a promising method to increase system throughput and reduce traffic load. Due to the characteristic of spectrum sharing in D2D network, confidentiality is becoming a key issue in content transmission. Secure communication in D2D networks is generally guaranteed by a physical-layer security mechanism. However, this method sacrifices the system transmission rate while ensuring security. Since mobile devices are carried by humans, we can leverage their trust relations to enhance the security of communications. As much, considering the psychology structure and social attributes of mobile users, we build a multidimensional trust evaluation mechanism to evaluate the trust relationship between users, and we pick out the trusted users based on the decisiontheoretic rough sets. By sharing content only between trust users, we can enhance the security of content transmissions without relying on physicallayer security measures. Meanwhile, content caching is now widely used to improve accessing efficiency and reduce traffic load on cellular networks. However, caching content for other users incurs additional cost, which results in selfish and noncooperative behavior in users. Considering such selfishness, we introduce a cooperative caching game based on multidimensional trust relations to motivate users to cache contents for other devices. In this game, the trust relations and physical distance between two users are considered to formulate the cost function. Furthermore, we introduce an incentive caching algorithm based on social trust to minimize the total cost in the D2D network. K E Y W O R D Scooperative game, D2D communications, incentive caching, social trust

5G-EECC: Energy-Efficient Collaboration-Based Content Sharing Strategy in Device-to-Device Communication

“…Figures 8 and 9 illustrate that the differences in delay when 3 gigabytes and 4 gigabytes of video content are divided into chunks and transmitted by four adjacent devices. Figure 8 shows that the cumulative percentage delay of our proposed approach improves 1.06% and 1.03% for the selected four (19) return requested D i (20) else (21) Send data creation_packet msg (data item) to base station (22) if (helper energy > threshold energy && helper capacity > threshold capacity) ( 23) then (24) Base station sorts helper in ascending order based on energy and capacity and distributes content ( 25) else (26) return requested D i from base station (27) end if (28) end if (29) end if (30) end if ALGORITHM 3: Cache discovery in D2D. devices as compared to the state-of-the-art D2D Comp and traditional D2D approaches, respectively.…”

“…In order to ensure reliable content sharing, a trust evaluation mechanism was presented for evaluating the cooperative capability, choice similarity, and social solidarity between mobile users [21][22][23][24]. e motivation problem in content caching was examined, and a cooperative caching game based on social trust was proposed.…”

“…One demander can receive content from one provider. Communication devices with high link quality and social ties were preferred, which enhanced battery usage but at the same time resulted in resources wastage [18][19][20][21][22][23][24][25][26][27][28].…”

“…is section introduces the design of the caching replacement strategy. A good cache replacement strategy tends to keep cached videos as long available as possible in (16) CH � id; (17) helper � 0; (18) CH send "CHMSG" to neighbor ]]; (20) end for (21) for i � 1 to K Do (22) then (23) if ne i ∈ N[CH] receive "CHMSG" ( 24) then (25) Stop cluster head selection and become member of cluster (26) if ne i ∈ N[CH] energy > threshold energy && ne i ∈ N[CH] capacity > threshold capacity ( 27) then (28) CH sort helper in ascending order based on energy and capacity ( 29) else (30) Nodes become ordinary member (31) end if (32) else (33) Continue the near future. According to our proposed design, cache index lists are divided into different levels with different cache priority.…”

Social Groups Based Content Caching in Wireless Networks

“…In [2] influential nodes are identified as caching locations that will serve their social friends via D2D communications. A more recent approach for D2D caching exploits the knowledge of pairwise social interactions [13]. In [15,18] a game-theoretic approach is proposed for mobile users to cache contents, both for themselves and for their friends.…”