Browsing by Author "Shamsi, Davood"

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Lifetime Optimization Using Energy Allocation in Wireless Ad-hoc Networks
    (2008-02-12) Koushanfar, Farinaz; Shamsi, Davood
    We develop energy-balancing strategies for wireless ad-hoc networks energy resource allocation and deployment. The objective is to extend the network lifetime. We find the amount of energy storage that each node requires for having a balanced energy consumption throughout the network. For a limited set of energy resources in the deployment area, we determine an efficient deployment scenario in which messages are routed across the network while using the fastest delivery path. Two ad-hoc architectures are considered: first, where the network is peerto-peer and all the nodes have the same characteristics; and second, a base-station centric network where a base-station in the center collects the data from the ad-hoc nodes. We study synchronous and asynchronous communication paradigms for both architectures. To address the problems, we first determine the deployment scheme that results in the most comprehensive radio coverage. Next, we calculate the energy distribution for each network scenario. Then, the derived distributions are extended to randomly deployed networks. We present a thorough analysis and comparison for peer-to-peer and base-station architectures, for both synchronous and asynchronous paradigms. Our experimental evaluations show that the energy-balancing distributions extend the network’s lifetime by more than 40% when compared to nonbalanced networks with no overhead on message routing delay.
  • Thumbnail Image
    Item
    Non-invasive IC tomography using spatial correlations
    (2010) Shamsi, Davood; Koushanfar, Farinaz
    We introduce a new methodology for post-silicon characterization of the gate-level variations in a manufactured Integrated Circuit (IC). The estimated characteristics are based on the power and the delay measurements that are affected by the process variations. The power (delay) variations are spatially correlated. Thus, there exists a basis in which variations are sparse. The sparse representation suggests using the L1-regularization (the compressive sensing theory). We show how to use the compressive sensing theory to improve post-silicon characterization. We also address the problem by adding spatial constraints directly to the traditional L2-minimization. The proposed methodology is fast, inexpensive, non-invasive, and applicable to legacy designs. Noninvasive IC characterization has a range of emerging applications, including post-silicon optimization, IC identification, and variations' modeling/simulations. The evaluation results on standard benchmark circuits show that, in average, the gate level characteristics estimation accuracy can be improved by more than two times using the proposed methods.