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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 © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

SUMMARY Internet of Things and broadband communication are promoting the pervasive mobile services with their advanced features. However, security problems baffled the development. This paper proposes a trust model to protect the user's security. The billing or trust operator works as an agent to provide a trust authentication for all the service providers. The services are classified by sensitive value calculation. With the combined location-aware and identity-aware information and authentication history, the user's trustiness for corresponding service can be obtained. For decision, three trust regions are divided and referred to three ranks as follows: high, medium and low. The trust region tells the customer which authentication methods should be used for access. Penalty coefficient is also involved for forbidding force-crack. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

SUMMARY In wireless mesh networks (WMNs), if nonoverlapped channels or partially overlapped channels are used properly, the throughput can be improved drastically. However, the number of nonoverlapped channels is limited in wireless communication standards. An effective channel assignment algorithm for a WMN is necessary to increase the utilization rate of space and nonoverlapped channels. Static channel assignment algorithms can improve network throughput, but their accuracies are not satisfactory in common scenarios. Dynamic channel assignment algorithms can allocate channels according to the status of adjacent links in WMNs. A dynamic channel assignment algorithm needs cross-layer design to get the information of routing. A routing-information-aware channel assignment algorithm based on a cross-layer design is proposed, which is named R-CA. The proposed method can dynamically allocate channels for wireless nodes when they need communication and release channels after data transmission. In R-CA, limited channel resources can be used efficiently by more wireless nodes, and hence the communication throughput can be improved. Simulation results show that our channel allocation strategy can effectively ensure and enhance the network throughput and packet delivery rate in WMNs. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

SUMMARY Localization based on received signal strength indication (RSSI) is a low cost and low complexity technology, and it is widely applied in distance-based localization of wireless sensor networks. The error of existing localization technologies is significant. This paper presents the N-times trilateral centroid weighted localization algorithm, which can reduce the error considerably. Considering the instability of RSSI, we use the weighted average of many RSSIs as current RSSI. To improve the accuracy, we select a number of (no less than three) reliable beacon nodes to increase the localization times. Then we calculate the distances between reliable beacon nodes and the mobile node using an empirical formula. The mobile node is located N times using the trilateral centroid algorithm. Finally, we take the weighted average of the filtered reference coordinates as the mobile node's coordinates. We conduct experiments with the STM32W108 chip, which supports IEEE 802.15.4. The results show that the proposed algorithm performs better than the trilateral centroid algorithm. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]