Qiuyuan Yang

Bio-inspired packet dropping for ad-hoc social networks

SUMMARY Ad-hoc social networks (ASNETs) explore social properties of nodes in communications. The usage of various social applications in a resource-scarce environment and the dynamic nature of the network create unnecessary congestion that might degrade the quality of service dramatically. Traditional approaches use drop-tail or random-early discard techniques to drop data packets from the intermediate node queue. Nonetheless, because of the unavailability of the social properties, these techniques are not suitable for ASNETs. In this paper, we propose a Bio-inspired packet dropping (BPD) algorithm for ASNETS. BPD imitates the matching procedure of receptors and epitopes in immune systems to detect congestions. The drop probability settings depend on the selection of data packets, which is based on node popularity level. BPD selects the most prioritized node through social properties, which is inspired by the B-cell stimulation in immune systems. To fairly prioritize data packets, two social properties are used: (1) similarity and (2) closeness centrality between nodes. Extensive simulations are carried out to evaluate and compare BPD to other existing schemes in terms of mean goodput, mean loss rate, throughput, delay, attained bandwidth, and overhead ratio. The results show that the proposed scheme outperforms these existing schemes. Copyright

Data dissemination using interest-tree in socially aware networking

Interrelation between interests and its impact on data dissemination is explored.A layered structure is presented to model various relationships between interests.An Interest-Tree based data dissemination scheme is proposed to improve efficiency.Extensive simulations verify performance and effectiveness of the proposed scheme. Socially aware networking (SAN) exploits social characteristics of mobile users to streamline data dissemination protocols in opportunistic environments. Existing protocols in this area utilized various social features such as user interests, social similarity, and community structure to improve the performance of data dissemination. However, the interrelationship between user interests and its impact on the efficiency of data dissemination has not been explored sufficiently. In this paper, we analyze various kinds of relationships between user interests and model them using a layer-based structure in order to form social communities in SAN paradigm. We propose Int-Tree, an Interest-Tree based scheme which uses the relationship between user interests to improve the performance of data dissemination. The core of Int-Tree is the interest-tree, a tree-based community structure that combines two social features, i.e., density of a community and social tie, to support data dissemination. The simulation results show that Int-Tree achieves higher delivery ratio, lower overhead, in comparison to two benchmark protocols, PROPHET and Epidemic routing. In addition, Int-Tree can perform with 1.36 hop counts in average, and tolerable latency in terms of buffer size, time to live (TTL) and simulation duration. Finally, Int-Tree keeps stable performance with various parameters.

Poster: reliable TCP for popular data in socially-aware ad-hoc networks

Reliable social connectivity and transmission of data for popular nodes are vital in multihop Ad-hoc Social Networks (ASNETs). However, congestion may occur and hence popular nodes might not achieve required bandwidth when multiple senders share data with a single receiver. The traditional Transport Control Protocol (TCP) might not be able to perform efficiently in ASNETs. Therefore, we propose a Reliable TCP for Popular Data in Socially-aware Ad-hoc Networks called RTPS. RTPS employs a popularity level approach for every single node which partitions the bandwidth among users. The reliability of popular data is ensured since bandwidth will firstly assigned to the popular sender. Preliminary results show that by delaying the acknowledgment and improving the performance of TCP, RTPS reduces collision loss in multihop ASNETs.

A social popularity aware scheduling algorithm for ad-hoc social networks

In an ad-hoc social network (ASNET), users normally require scheduling popular data packet first. However, ASNET users have some limitations due to the scarce bandwidth and unreliability in wireless connection. Traditional algorithms use First In First Out (FIFO) order for scheduling, which is not suitable in ASNETs and cannot work properly with congested environments. To overcome the above mentioned problems, in this paper, we introduce a social popularity aware scheduling algorithm in the context of ad-hoc social networks, namely Pop-aware. Pop-aware provides solution after calculating the traffic load of intermediate node and assigns priority to incoming flow using degree centrality (social property). It provides fairness in received service to each flow using the active service rate concept. Experimental results show that the performance of Pop-aware is better as compared against existing schemes, in terms of average throughput, packet loss rate and average delay.

Poster: CIS: a community-based incentive scheme for socially-aware networking

To address selfishness in socially-aware networking, we propose a Community-based Incentive Scheme (CIS). CIS utilizes community to stimulate cooperation among selfish nodes and allows all nodes to behave selfishly to imitate the realistic condition. The simulation results show that CIS effectively stimulates selfish nodes to cooperate, achieves higher delivery ratio while not increasing latency dramatically.

ComPAS: maximizing data availability with replication in ad-hoc social networks

Although existing replica allocation protocols perform well in most cases, some challenges still need to be addressed to further improve their performance. The success of such protocols for Ad-hoc Social Networks (ASNETs) depends on the performance of data accessibility and on the easy consistency management of available replica. We contribute to this line of research with replication protocol for maximizing availability of a data. Essentially, we propose ComPAS, a community-partitioning aware replica allocation method. Its goals include integration of social relationship for placing copy of the data in the community to achieve better efficiency and consistency by keeping the replica read cost, relocation cost and traffic as low as possible.