On greedy construction of connected dominating sets in wireless networks
Since no fixed infrastructure and no centralized management present in wireless networks, a connected dominating set (CDS) of the graph representing the network is widely used as a virtual backbone. Constructing a minimum CDS is NP-hard. In this paper, we propose a new greedy algorithm, called S-MIS, with the help of Steiner tree that can construct a CDS within a factor of 4:8 þ ln5 from the optimal solution. We also introduce the distributed version of this algorithm. We prove that the proposed algorithm is better than the current best performance ratio which is 6.8. A simulation is conducted to compare S-MIS with its variation which is rS-MIS. The simulation shows that the sizes of the CDSs generated by S-MIS and rS-MIS are almost the same.

title: Greedy Approximation Algorithms
abstract: Greedy strategy is a simple and natural method in the design of approximation algorithms. This chapter presents greedy approximation algorithms for very broad classes of maximization problems and minimization problems and analyzes their approximation bounds. A number of applications of these greedy approximation algorithms are also described in this chapter. For many applications, the greedy approximation algorithm can achieve the best known approximation bound in a straightforward manner. For some applications, they have different formulations, and the corresponding greedy approximation algorithms have different approximation bounds. In addition, some applications can have better approximation algorithm than the greedy approximation algorithm.

title: Optimization scheme for sensor coverage scheduling with bandwidth constraints
abstract: 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: On the construction of 2-connected virtual backbone in wireless networks
abstract: Virtual backbone has been proposed as the routing infrastructure to alleviate the broadcasting storm problem in ad hoc networks. Since the nodes in the virtual backbone need to carry other node's traffic, and node and link failure are inherent in wireless networks, it is desirable that the virtual backbone is fault tolerant. In this paper, we propose a new algorithm called Connecting Dominating Set Augmentation (CDSA) to construct a 2-connected virtual backbone which can resist the failure of one wireless node. We show that CDSA has guaranteed quality by proving that the size of the CDSA constructed 2-connected backbone is within a constant factor of the optimal 2-connected virtual backbone size. Through extensive simulations, we demonstrate that in practice, CDSA can build a 2-connected virtual backbone with only small overhead.

title: Coverage problems in wireless sensor networks: designs and analysis
abstract: One fundamental problem in wireless sensor networks is the coverage problem, which reflects the quality of service that can be provided by a particular sensor network. The coverage problem is defined from several points of view due to a variety of sensor networks and a wide-range of their applications. Several different designs and formulations of the coverage problem have been proposed. They are subject to various topics such as types of interest regions (areas versus targets) and different network constraints, such as fault tolerance and bandwidth limitation. In this paper, we survey the state-of-the-art coverage formulations with an objective of maximising network lifetime. In particular, we present an overview and analysis of the solutions proposed in recent research literature.

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: 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: 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: Using MEMS-based storage in computer systems---MEMS storage architectures
abstract: As an emerging nonvolatile secondary storage technology, MEMS-based storage exhibits several desirable properties including high performance, high storage volumic density, low power consumption, low entry cost, and small form factor. However, MEMS-based storage provides a limited amount of storage per device and is likely to be more expensive than magnetic disk. Systems designers will therefore need to make trade-offs to achieve well-balanced designs. We present an architecture in which MEMS devices are organized into MEMS storage enclosures with online spares. Such enclosures are proven to be highly reliable storage building bricks with no maintenance during their economic lifetimes. We also demonstrate the effectiveness of using MEMS as another layer in the storage hierarchy, bridging the cost and performance gap between MEMS storage and disk. We show that using MEMS as a disk cache can significantly improve system performance and cost-performance ratio.

title: Using MEMS-based storage to boost disk performance
abstract: Non-volatile storage technologies such as flash memory, magnetic RAM (MRAM), and MEMS-based storage are emerging as serious alternatives to disk drives. Among these, MEMS storage is predicted to be the least expensive and highest density, and at about 1 ms access times still considerably faster than hard disk drives. Like the other emerging non-volatile storage technologies, it is highly suitable for small mobile devices but it is expensive to replace hard drives entirely. Its non-volatility, dense storage, and high performance still make it an ideal candidate for the secondary storage subsystem. We examine the use of MEMS storage in the storage hierarchy and show that using a technique called MEMS caching disk, we can achieve 30-49% of the pure MEMS storage performance by using only a small amount (3% of the disk capacity) of MEMS storage in conjunction with a standard hard drive. The resulting system is ideally suited for commercial packaging with a small MEMS device included as part of a standard disk controller or paired with a disk.