Optimization scheme for sensor coverage scheduling with bandwidth constraints
Wireless Sensor Network has attracted a lot of attentions due to its broad applications in recent years and also introduces many challenges. Network lifetime is a critical issue in Wireless Sensor Networks. It is possible to extend network lifetime by organizing the sensors into a number of sensor covers. However, with the limited bandwidth, coverage breach (i.e, targets that are not covered) can occur if the number of available time-slots/channels is less than the number of sensors in a sensor cover. In this paper, we study a joint optimization problem in which the objective is to minimize the coverage breach as well as to maximize the network lifetime. We show a “trade-off” scheme by presenting two strongly related models, which aim to tradeoffs between the two conflicting objectives. The main approach of our models is organizing sensors into non-disjoint sets, which is different from the current most popular approach and can gain longer network lifetime as well as less coverage breach. We proposed two algorithms for the first model based on linear programming and greedy techniques, respectively. Then we transform these algorithms to solve the second model by revealing the strong connection between the models. Through numerical simulation, we showed the good performance of our algorithms and the pictures of the tradeoff scheme in variant scenarios, which coincide with theoretical analysis very well. It is also showed that our algorithms could obtain less breach rate than the one proposed in (Cheng et al. in INFOCOM’ 05, 2005).

title: Improved construction for pooling design
abstract: Pooling design is a mathematical tool with many applications in molecular biology, specially to reduce the number of tests for DNA library screening. In this note, we study construction of pooling design and present an improvement to a recent new construction given by Du et al. ( 2006).

title: A Real-Time Network Traffic Profiling System
abstract: This paper presents the design and implementation of a real-time behavior profiling system for high-speed Internet links. The profiling system uses flow-level information from continuous packet or flow monitoring systems, and uses data mining and information-theoretic techniques to automatically discover significant events based on the communication patterns of end-hosts. We demonstrate the operational feasibility of the system by implementing it and performing extensive benchmarking of CPU and memory costs using a variety of packet traces from OC-48 links in an Internet backbone network. To improve the robustness of this system against sudden traffic surges such as those caused by denial of service attacks or worm outbreaks, we propose a simple yet effective filtering algorithm. The proposed algorithm successfully reduces the CPU and memory cost while maintaining high profiling accuracy.

title: Variation-aware task allocation and scheduling for MPSoC
abstract: As technology scales, the delay uncertainty caused by process variations has become increasingly pronounced in deep submicron designs. As a result, a paradigm shift from deterministic to statistical design methodology at all levels of the design hierarchy is inevitable . In this paper, we propose a variation-aware task allocation and scheduling algorithm for Multiprocessor System-on-Chip (MPSoC) architectures to mitigate the impact of parameter variations. A new design metric, called performance yield and defined as the probability of the assigned schedule meeting the predefined performance constraints, is used to guide the task allocation and scheduling procedure. An efficient yield computation method for task scheduling complements and significantly improves the effectiveness of the proposed variation-aware scheduling algorithm. Experimental results show that our variation-aware scheduler achieves significant yield improvements. On average, 45% and 34% yield improvements over worst-case and nominal-case deterministic schedulers, respectively, can be obtained across the benchmarks by using the proposed variation-aware scheduler.

title: Optimal topology exploration for application-specific 3D architectures
abstract: As technology scales, increasing interconnect costs make it necessary to consider alternate ways of building integrated circuits. One promising option along this direction is 3D architectures where a stack of multiple device layers, with direct vertical tunneling through them, are put together on the same chip. In this paper, we explore how processor cores and storage blocks can be placed in a 3D architecture to minimize data access costs under temperature constraints. This process is referred to as the topology exploration. Using integer linear programming, we compare the best 2D placement with the best 3D placement, and show through experiments with both single-core and multicore systems that the 3D placement generates much better results (in terms of data access costs) under the same temperature bounds. We also discuss the tradeoffs between temperature constraint and data access costs

title: Process-Variation-Aware Adaptive Cache Architecture and Management
abstract: Fabricating circuits that employ ever-smaller transistors leads to dramatic variations in critical process parameters. This in turn results in large variations in execution/access latencies of different hardware components. This situation is even more severe for memory components due to minimum-sized transistors used in their design. Current design methodologies that are tuned for the worst case scenarios are becoming increasingly pessimistic from the performance angle, and thus, may not be a viable option at all for future designs. This paper makes two contributions targeting on-chip data caches. First, it presents an adaptive cache management policy based on nonuniform cache access. Second, it proposes a latency compensation approach that employs several circuit-level techniques to change the access latency of select cache lines based on the criticalities of the load instructions that access them. Our experiments reveal that both these techniques can recover significant amount of the lost performance due to worst case designs.

title: Variability-driven module selection with joint design time optimization and post-silicon tuning
abstract: Increasing delay and power variation are significant challenges to the designers as technology scales to the deep sub-micron (DSM) regime. Traditional module selection techniques in high level synthesis use worst case delay/power information to perform the optimization, and therefore may be too pessimistic such that extra resources are used to guarantee design requirements. Parametric yield, which is defined as the probability of the synthesized hardware meeting the performance/power constraints, can be used to guide design space exploration. The parametric yield can be effectively improved by combining both design-time variation-aware optimization and post silicon tuning techniques (such as adaptive body biasing (ABB)). In this paper, we propose a module selection algorithm that combines design-time optimization with post- silicon tuning (using ABB) to maximize design yield. A variation-aware module selection algorithm based on efficient performance and power yield gradient computation is developed. The post silicon optimization is formulated as an efficient sequential conic program to determine the optimal body bias distribution, which in turn affects design-time module selection. The experiment results show that significant yield can be achieved compared to traditional worst-case driven module selection technique. To the best of our knowledge, this is the first variability-driven high level synthesis technique that considers post-silicon tuning during design time optimization.

title: Design Space Exploration for 3-D Cache
abstract: As technology scales, interconnects have become a major performance bottleneck and a major source of power consumption for sub-micro integrated circuit (IC) chips. One promising option to mitigate the interconnect challenges is 3D ICs, in which a stack of multiple device layers are put together on the same chip. In this paper, we explore the architectural design of cache memories using 3D circuits. We present a delay and energy model 3D cache delay-energy estimation tool (3D-Cacti) to explore different 3D design options of partitioning a cache. The tool allows partitioning of a cache across different device layers at various levels of granularity. The tool has been validated by comparing its results with those obtained from circuit simulation of custom 3D layouts. We also explore the effects of various cache partitioning parameters and 3D technology parameters on delay and energy to demonstrate the utility of the tool.