CTN Issue: February 2014

1. Efficiency Resource Allocation for Device-to-Device Underlay Communication Systems: A Reverse Iterative Combinatorial Auction Based Approach

Device-to-device (D2D) communication has been well recognized as a promising paradigm to improve user experiences in cellular networks by reusing licensed spectrum. However, design, analysis, and optimization of D2D communication require multidisciplinary knowledge, including wireless communication, signal processing, and economic theory. In this paper, the authors developed an innovative resource allocation scheme, to multiplex the communications of multiple D2D users with cellular users. The key idea is to use combinatorial auction theory for allocating radio resources when D2D communication works as an underlay, and investigate the interference relationship between D2D and cellular users.

Title and author(s) of the original paper in IEEE Xplore:
Title: Efficiency Resource Allocation for Device-to-Device Underlay Communication Systems: A Reverse Iterative Combinatorial Auction Based Approach
Author: Chen Xu, Lingyang Song, Zhu Han, Qun Zhao, Xiaoli Wang, Xiang Cheng, and Bingli Jiao
This paper appears in: IEEE Journal on Selected Areas in Communications
Issue Date: September 2013

2. Efficient Resource Provisioning and Rate Selection for Stream Mining in a Community Cloud

While the emerging mobile cloud technology provides a promising solution for mining big multimedia data in wireless networks, there exist several limitations imposed by the energy-constrained mobile devices, irresponsive delivery of mined stream, and huge drain on server-side resources. This paper proposes a mobile cloud-based stream mining system that addresses three key metrics: energy consumption of the cloud, accuracy of mining result and responsiveness, as well as the energy consumption of battery-powered mobile users. Since optimizing all metrics simultaneously is impossible in practice, the cloud operator needs to properly tradeoff these metrics. However, this is not straight forward as the environment in which the system operates randomly changes over time, and the distribution of the underlying stochastic process is often unknown a priori. To address these issues, the authors leverage state-of-the-art control techniques and develop an online computational resource provisioning and transmission rate selection algorithm to minimize the classification-energy cost. Each mobile user can thus decide its transmission rate, while the cloud operator decides its computational resource provisioning for stream mining. The distinguishing feature of online execution makes the proposed solution an appealing candidate for future mobile cloud supporting interactive stream mining and for realizing the full potential of big data in wireless networks.

This paper has also been recommended as a "Distinguished Paper" in the IEEE ComSoc MMTC Reviewer Letter in February 2014.

Title and author(s) of the original paper in IEEE Xplore:
Title: Efficient Resource Provisioning and Rate Selection for Stream Mining in a Community Cloud
Author: Shaolei Ren and van der Schaar, M.
This paper appears in: IEEE TRANSACTIONS ON MULTIMEDIA
Issue Date: June 2013

3. On Optimizing Green Energy Utilization for Cellular Networks with Hybrid Energy Supplies

This paper envisions a future cellular network where base stations (BSs) are powered by multiple types of energy sources, such as those from the traditional power grid, solar energy, and wind energy. This means that the BSs can reduce their carbon footprints if they have enough green energy stored in their batteries. Otherwise, BSs can be switched to on-grid energy to serve mobile users. Such reduction of the BSs’ power consumption is crucial to green cellular networks, since BSs consume more than 50% of the total energy of cellular networks. In order to reduce the on-grid energy consumption of cellular networks during the peak traffic hours, this work studied the green energy optimization (GEO) problem to balance the energy consumption among BSs. To solve the problem, this paper decomposed the GEO problem into two sub-problems, in the time dimension and the spatial dimension, respectively, the multi-stage energy allocation (MEA) problem and the multi-BSs energy balancing (MEB) problem based on the characteristics of green energy generation and mobile traffic. The authors provided theoretical analysis and extensive simulations to demonstrate that the proposed scheme is able to save a significant amount of on-grid energy.

This paper has also been recommended as a "Distinguished Paper" in the IEEE ComSoc MMTC Reviewer Letter in February 2014.

Title and author(s) of the original paper in IEEE Xplore:
Title: On Optimizing Green Energy Utilization for Cellular Networks with Hybrid Energy Supplies
Author: Tao Han and Nirwan Ansari
This paper appears in: IEEE Transactions on Wireless Communications
Issue Date: August 2013

4. Dependable Demand Response Management in the Smart Grid: A Stackelberg Game Approach

The authors model the interactions between utility companies and end-users, and propose a Stackelberg game based demand response management (DRM) scheme for the smart grid. Smart grid includes a metering infrastructure capable of sensing and measuring power consumption from consumers integrated with advanced information and communication technologies. DRM is a key feature of the smart grid, and it focuses on managing the changes in consumers’ energy usage in response to changes in the electricity price over time. The main challenge of designing effective DRM mechanisms is to have a fundamental understanding of the complicated interactions among different components in the smart grid. The model proposed in paper successfully captures such interactions. The proposed scheme reduces the consumers’ electricity bill, decreases the cost of power generators, and balances the power demand and the power supply through the real-time pricing. An important observation in this work is the potential attack on the smart meters infrastructure and its consequences. The authors develop energy-storage-based mechanisms to maintain the reliability and resilience of the grid in the presence of an attacker, thus making the smart grid a dependable system.

Title and author(s) of the original paper in IEEE Xplore:
Title: Dependable Demand Response Management in the Smart Grid: A Stackelberg Game Approach
Author: S. Maharjan, Q. Zhu, Y. Zhang, S. Gjessing, and T. Basar
This paper appears in: IEEE Transactions on Smart Grid
Issue Date: March 2013

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