Dynamic Power Splitting Policies for AF Relay Networks with Wireless Energy Harvesting

Wireless energy harvesting (WEH) provides an exciting way to supply energy for relay nodes to forward information for the source-destination pairs. In this paper, we investigate the problem on how the relay node dynamically adjusts the power splitting ratio of information transmission (IT) and energy harvesting (EH) in order to achieve the optimal outage performance. According to the knowledge of channel state information (CSI) at the relay, optimal dynamic power splitting policy with full CSI and partial CSI are both provided. Finally, through simulations, the proposed power splitting policies can improve the outage performances and the policy with full CSI achieves the best performance. It is also shown that the policy with partial CSI can approach the policy with full CSI closely and incurs far less system overhead.Comment: accepted by IEEE ICC 2015 - Workshop on Green Communications and Networks with Energy Harvesting, Smart Grids, and Renewable Energie

Protecting 802.11-Based Wireless Networks From SCTS and JACK Attacks

The convenience of IEEE 802.11-based wireless access networks has led to widespread deployment. However, these applications are predicated on the assumption of availability and confidentiality. Error-prone wireless networks afford an attacker considerable flexibility to exploit the vulnerabilities of 802.11-based mechanism. Two of most famous misbehaviors are selfish and malicious attacks. In this thesis we investigate two attacks: Spurious CTS attack (SCTS) and Jamming ACK attack (JACK). In the SCTS, malicious nodes may send periodic Spurious CTS packets to force other nodes to update their NAV values and prevent them from using the channel. In the JACK, an attacker ruins legitimate ACK packets for the intention of disrupting the traffic flow and draining the battery energy of victim nodes quickly. Correspondingly, we propose solutions: termed Carrier Sensing based Discarding (CSD), and Extended Network Allocation Vector (ENAV) scheme. We further demonstrate the performance of our proposed schemes through analysis and NS2 simulations

Faster Random Walks By Rewiring Online Social Networks On-The-Fly

Many online social networks feature restrictive web interfaces which only allow the query of a user's local neighborhood through the interface. To enable analytics over such an online social network through its restrictive web interface, many recent efforts reuse the existing Markov Chain Monte Carlo methods such as random walks to sample the social network and support analytics based on the samples. The problem with such an approach, however, is the large amount of queries often required (i.e., a long "mixing time") for a random walk to reach a desired (stationary) sampling distribution. In this paper, we consider a novel problem of enabling a faster random walk over online social networks by "rewiring" the social network on-the-fly. Specifically, we develop Modified TOpology (MTO)-Sampler which, by using only information exposed by the restrictive web interface, constructs a "virtual" overlay topology of the social network while performing a random walk, and ensures that the random walk follows the modified overlay topology rather than the original one. We show that MTO-Sampler not only provably enhances the efficiency of sampling, but also achieves significant savings on query cost over real-world online social networks such as Google Plus, Epinion etc.Comment: 15 pages, 14 figure, technical report for ICDE2013 paper. Appendix has all the theorems' proofs; ICDE'201