Advances in wireless technologies in the last ten years have created considerable opportunities as well as challenges for wireless body medical systems. The foremost challenge is how to build a reliable system connecting heterogeneous body sensors and actuators in an open system environment. In this dissertation, we present our work towards this goal. The system addresses four design issues: the underlying network architecture, the network scheduling disciplines, the location determination and tracking methods, and the embedded application execution architecture. We first present the design of an adaptive wireless protocol (MBStarPlus) to provide the basic wireless platform WBAN (Wireless Body Area Network). MBStarPlus is a real-time, secure, robust and flexible wireless network architecture. It is designed to utilize any low-power wireless radio as its physical layer. The TDMA mechanism is adopted for realtime data delivery. The time-slot length is adjustable for flexibility. Multiple technologies are utilized to provide reliability and security. We next investigate how to coordinate the body sensors/actuators that can optimally select from a range (maximum and minimum) of data rates. Two bandwidth scheduling algorithms are proposed. One is a greedy algorithm that works for sensors with limited computational capability. The other is the UMinMax scheduling algorithm that has better scalability and power-saving performance but is more computationally intensive. The third issue addressed in this proposal is how to achieve location determination and tracking by a mix of high-precision but expensive and lower-precision but cost-effective sensors. This is achieved by a novel collaborative location determination scheme ColLoc that can integrate different types of distance measurements into a location estimation algorithm by weighing them according to their precision levels. Through this, a localization service can be both cost-effective and sufficiently accurate. Fourth, in order to minimize the effects of long network latency when the body network scales up, we propose ControlInGateway, an architectural feature that allows a control application to be executed inside the network gateway without the host's involvement. With ControlInGateway, a wireless system could achieve the same control quality as a wired system. / text

Many next-generation e-science applications require fast and reliable transfer of large volumes of data, now frequently termed as ``big data", with guaranteed performance, which is typically enabled by the bandwidth reservation service in high-performance networks (HPNs). Users normally specify the properties and requirements of their data transfers in the bandwidth reservation requests (BRRs), and want to make bandwidth reservations on the HPNs to satisfy the requirements of their data transfers. The challenges of the bandwidth reservation arise from the requirements desired by both the users and the bandwidth reservation service providers of the HPNs. We focus on two important bandwidth reservation problems formulated from the combinations of the requirements from both users and the bandwidth reservation service providers of the HPNs: (i) Problem of scheduling all BRRs in one batch while achieving their best average data transfer earliest completion time and shortest duration, and (ii) Problem of scheduling two generic types of BRRs concerning data transfer reliability with different objectives and constraints in unreliable HPNs that are subject to node and link failures. We prove the two subproblems of the first problem are NP-complete problems, and fast and efficient heuristic algorithms are proposed. While the two subproblems of the second problem can be optimally solved in polynomial time. The corresponding optimal algorithms and proofs are given. We conduct extensive simulations to compare the performance of the proposed heuristic and optimal algorithms with naive scheduling algorithms and the algorithms currently used in production network in various performance metrics. The performance superiority of the proposed heuristic and optimal algorithms is verified.