Pi-Cheng Hsiu

Distributed Throughput Optimization for ZigBee Cluster-Tree Networks

ZigBee, a unique communication standard designed for low-rate wireless personal area networks, has extremely low complexity, cost, and power consumption for wireless connectivity in inexpensive, portable, and mobile devices. Among the well-known ZigBee topologies, ZigBee cluster-tree is especially suitable for low-power and low-cost wireless sensor networks because it supports power saving operations and light-weight routing. In a constructed wireless sensor network, the information about some area of interest may require further investigation such that more traffic will be generated. However, the restricted routing of a ZigBee cluster-tree network may not be able to provide sufficient bandwidth for the increased traffic load, so the additional information may not be delivered successfully. In this paper, we present an adoptive-parent-based framework for a ZigBee cluster-tree network to increase bandwidth utilization without generating any extra message exchange. To optimize the throughput in the framework, we model the process as a vertex-constraint maximum flow problem, and develop a distributed algorithm that is fully compatible with the ZigBee standard. The optimality and convergence property of the algorithm are proved theoretically. Finally, the results of simulation experiments demonstrate the significant performance improvement achieved by the proposed framework and algorithm over existing approaches.

Age-based PCM wear leveling with nearly zero search cost

Improving the endurance of PCM is a fundamental issue when the technology is considered as an alternative to main memory usage. In the design of memory-based wear leveling approaches, a major challenge is how to efficiently determine the appropriate memory pages for allocation or swapping. In this paper, we present an efficient wear-leveling design that is compatible with existing virtual memory management. Two implementations, namely, bucket-based and array-based wear leveling, with nearly zero search cost are proposed to tradeoff time and space complexity. The results of experiments conducted based on popular benchmarks to evaluate the efficacy of the proposed design are very encouraging.

A Mobility-Aware Node Deployment and Tree Construction Framework for ZigBee Wireless Networks

ZigBee is a specification formalized by the IEEE 802.15.4 standard for low-power low-cost low-data-rate wireless personal area networks. In ZigBee networks, a tree topology is often used to construct a wireless sensor network for data delivery applications. However, delivery failures constantly occur in ZigBee wireless applications due to node movements and network topology changes. The conventional route reconstruction method is designed to mitigate the effects of topology changes, but it consumes a large amount of resources. In this paper, we exploit the regularity in node mobility patterns to reduce the frequency of route reconstructions and ensure that the transmission of data to mobile nodes is efficient. To increase the data delivery ratio and mitigate the effects of packet loss caused by the node mobility, we propose a ZigBee node deployment and tree construction framework. In particular, the framework considers the regularity in mobility patterns during the construction of the routing tree and deployment of nodes. It also includes an overhearing mechanism for mobile nodes to further improve the data delivery ratio. We present details of the proposed algorithms for node deployment and tree construction in the framework. The effectiveness of network topologies constructed under the framework is demonstrated through comprehensive ns-2 simulations based on two real-world scenarios. The results show that our approach can construct ZigBee tree topologies with a high data delivery ratio and low routing overhead.

Energy-Efficient Video Multicast in 4G Wireless Systems

Layer-based video coding, together with adaptive modulation and coding, is a promising technique for providing real-time video multicast services on heterogeneous mobile devices. With the rapid growth of data communications for emerging applications, reducing the energy consumption of mobile devices is a major challenge. This paper addresses the problem of resource allocation for video multicast in fourth-generation wireless systems, with the objective of minimizing the total energy consumption for data reception. First, we consider the problem when scalable video coding is applied. We prove that the problem is NP-hard and propose a 2-approximation algorithm to solve it. Then, we investigate the problem under multiple description coding, and show that it is also NP-hard and cannot be approximated in polynomial time with a ratio better than 2, unless P = NP. To solve this case, we develop a pseudopolynomial time 2-approximation algorithm. The results of simulations conducted to compare the proposed algorithms with a brute-force optimal algorithm and a conventional approach are very encouraging.

Search-Oriented Deployment Strategies for Wireless Sensor Networks

Wireless sensor networks have been widely considered as an effective tool in various application domains. One of the major implementation issues is on the network deployment problem. In this paper, we target issues in the deployment of wireless sensor nodes in three-dimensional indoor environments and with irregular radiation patterns for both message communicating and sensing. Our objective is to develop a more effective way to deploy sensor networks and to minimize the number of deployed nodes. We propose several search-oriented strategies to improve the performance of search algorithms, such as simulated annealing. The capability of the proposed strategies is demonstrated by real-case studies in the deployment of sensor networks in several office flats

Dynamic Backlight Scaling Optimization: A Cloud-Based Energy-Saving Service for Mobile Streaming Applications

With the increasing variety of mobile applications, reducing the energy consumption of mobile devices is a major challenge in sustaining multimedia streaming applications. This paper explores how to minimize the energy consumption of the backlight when displaying a video stream without adversely impacting the users visual experience. First, we model the problem as a dynamic backlight scaling optimization problem. Then, we propose algorithms to solve the fundamental problem and prove the optimality in terms of energy savings. Finally, based on the algorithms, we present a cloud-based energy-saving service. We have also developed a prototype implementation integrated with existing video streaming applications to validate the practicability of the approach. The results of experiments conducted to evaluate the efficacy of the proposed approach are very encouraging and show energy savings of 15-49 percent on commercial mobile devices.

Dynamic backlight scaling optimization for mobile streaming applications

With the increasing variety of mobile applications, reducing the energy consumption of mobile devices is a major challenge in sustaining multimedia streaming applications. This paper explores backlight scaling, which is deemed a promising technical solution. First, we model the problem as a dynamic backlight scaling optimization problem. The objective is to minimize the energy consumption of the backlight when displaying a video stream without adversely impacting the users visual perception. Then, we propose a dynamic-programming algorithm to solve the fundamental problem and prove its optimality in terms of energy savings. Finally, based on the algorithm, we consider implementation issues. We have also developed a prototype implementation integrated with existing video streaming services to validate the practicability of the approach. The results of experiments conducted to demonstrate the efficacy of the proposed algorithm are very encouraging.

User-Centric Energy-Efficient Scheduling on Multi-Core Mobile Devices

Mobile devices will provide improved computing resources to sustain progressively more complicated applications. However, the design concept of fair scheduling and governing borrowed from legacy operating systems cannot be applied seamlessly in mobile systems, thereby degrading user experience or reducing energy efficiency. In this paper, we posit that mobile applications should be treated unfairly. To this end, we exploit the concept of application sensitivity and devise a user-centric scheduler and governor that allocate computing resources to applications according to their sensitivity. Furthermore, we integrate our design into the Android operating system. The results of extensive experiments on a commercial smartphone with real-world mobile apps demonstrate that the proposed design can achieve significant energy efficiency gains while improving the quality of user experience.

Mobility-aware charger deployment for wireless rechargeable sensor networks

Wireless charging technology is considered as one of the promising solutions to solve the energy limitation problem for large-scale wireless sensor networks. Obviously, charger deployment is a critical issue since the number of chargers would be limited by the network construction budget, which makes the full-coverage deployment of chargers infeasible. In many of the applications targeted by large-scale wireless sensor networks, end-devices are usually equipped by the human and their movement follows some degree of regularity. Therefore in this paper, we utilize this property to deploy chargers with partial coverage, with an objective to maximize the survival rate of end-devices. We prove this problem is NP-hard, and propose an algorithm to tackle it. The simulation results show that our proposed algorithm can significantly increase the survival rate of end-devices. To our knowledge, this is one of very first works that consider charger deployment with partial coverage in wireless rechargeable sensor networks.

Compliance Enforcement of Temporal and Dosage Constraints

Medication dispensers treated in this paper are designed to help improve compliance by users who live at homes and take medications over long periods of time. The paper first presents an overview of medication specifications that define constraints for dispensers and dispenser components that administer medications as specified. When given a specification and constraints defined by it, the dispenser scheduler checks for consistency and feasibility of constraints and schedules medications to meet the constraints. Several basic algorithms needed for these purposes are described and evaluated