Big Data Computing and Communications: First International by Yu Wang, Hui Xiong, Shlomo Argamon, XiangYang Li, JianZhong

By Yu Wang, Hui Xiong, Shlomo Argamon, XiangYang Li, JianZhong Li

This booklet constitutes the lawsuits of the 1st foreign convention on colossal info Computing and Communications, BigCom 2015, held in Taiyuan, China, in August 2015. The forty-one papers offered during this quantity have been rigorously reviewed and chosen from seventy four submissions. They have been equipped in topical sections named: instant verbal exchange and networks; database and large information; clever cellphone and sensing software; safety and privateness; structure and functions; sensor networks and RFID; social networks and advice; sign processing and development popularity; and routing and source management.

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Extra info for Big Data Computing and Communications: First International Conference, BigCom 2015, Taiyuan, China, August 1-3, 2015, Proceedings

Example text

Proof: In order to prove an auction mechanism is individual rational, that is, no participants will get a negative utility, we will prove that no buyer will pay more than its valuation, and no seller will be paid less than its valuation. Obviously, a buyer or seller who fails in the auction will not pay or be paid any fee, the utility of them is always equal to 0. So individual rationality is guaranteed in this situation. First, we should prove the buyers are individual rational in RTDA. According to the design of WDP in the second step, buyers are sorted in a descending order of bids.

References 1. : Compressed channel sensing: A new approach to estimating sparse multipath channels. Proceedings of the IEEE 98(6), 1058–1076 (2010) 2. : Compressive sampling. In: Proceedings of the International Congress of Mathematicians, Madrid, Spain, vol. 3, pp. 1433–1452 (2006) 3. : Methods for sparse signal recovery using kalman filtering with embedded pseudo-measurement norms and quasi-norms. IEEE Transactions on Signal Processing 58(4), 2405–2409 (2010) 4. : Optimal pilot placement for time-varying channels.

Each buyer will ask for at least one time slot of one channel by random distribution. • Interference Condition. We assume that our experiments are under cluster network topology. We randomly place 50% buyers in the center of a given area to create a hot-spot and randomly deploy the rest 50% buyers in the whole space. Second, we define two parameters to show the performance of RTDA. 24 F. Tian et al. • Average Usage Rate f . The usage rate of a channel can be defined as the number of the time slots which have been sold divided by the total number of the time slots of one channel.

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