41006390
Min-energy voltage allocation for tree-structured tasks
We study job scheduling on processors capable of running at variable voltage/speed to minimize energy consumption. Each job in a problem instance is specified by its arrival time and deadline, together with required number of CPU cycles. It is known that the minimum energy schedule for n jobs can be computed in O(n3) time, assuming a convex energy function. We investigate more efficient algorithms for computing the optimal schedule when the job sets have certain special structures. When the time intervals are structured as trees, the minimum energy schedule is shown to have a succinct characterization and is computable in time O(P) where P is the tree’s total path length. We also study an on-line average-rate heuristics AVR and prove that its energy consumption achieves a small constant competitive ratio for nested job sets and for job sets with limited overlap. Some simulation results are also given.
3605809
Performance evaluation for energy efficient topologic control in ad hoc wireless networks
Minimizing total energy to keep an ad hoc wireless network symmetrically connected is an NP-hard problem. Recently, several greedy approximations have been proposed, based on k-restricted decompositions of the network. Their performance ratios are established through estimations of the least upper bound ρk for the ratio between total powers of best possible k-restricted decomposition and the optimal solution. In this paper, we determine the exact value of ρk for all k.
15017510
Min-Energy Voltage Allocation for Tree-Structured Tasks
We study job scheduling on processors capable of running at variable voltage/speed to minimize energy consumption. Each job in a problem instance is specified by its arrival time and deadline, together with required number of CPU cycles. It is known that the minimum energy schedule for n jobs can be computed in O(n3) time, assuming a convex energy function. We investigate more efficient algorithms for computing the optimal schedule when the job sets have certain special structures. When the time intervals are structured as trees, the minimum energy schedule is shown to have a succinct characterization and is computable in time O(P) where P is the tree’s total path length. We also study an on-line average-rate heuristics AVR and prove that its energy consumption achieves a small constant competitive ratio for nested job sets and for job sets with limited overlap. Some simulation results are also given.
6072229
PRESTO: feedback-driven data management in sensor networks
This paper presents PRESTO, a novel two-tier sensor data management architecture comprising proxies and sensors that cooperate with one another for acquiring data and processing queries. PRESTO proxies construct time-series models of observed trends in the sensor data and transmit the parameters of the model to sensors. Sensors check sensed data with model-predicted values and transmit only deviations from the predictions back to the proxy. Such a model-driven push approach is energy-efficient, while ensuring that anomalous data trends are never missed. In addition to supporting queries on current data, PRESTO also supports queries on historical data using interpolation and local archival at sensors. PRESTO can adapt model and system parameters to data and query dynamics to further extract energy savings. We have implemented PRESTO on a sensor testbed comprising Intel Stargates and Telos Motes. Our experiments show that in a temperature monitoring application, PRESTO yields one to two orders of magnitude reduction in energy requirements over on-demand, proactive or model-driven pull approaches. PRESTO also results in an order of magnitude reduction in query latency in a 1% duty-cycled five hop sensor network over a system that forwards all queries to remote sensor nodes.
42814281
Fixed Topology Alignment with Recombination
In this paper, we study a new version of multiple sequence alignment, fixed topology alignment with recombination. We show that it can not be approximated within any constant ratio unless P = NP. For a more restricted version, we show that the problem is MAX-SNP-hard. This implies that there is no PTAS for this version unless P = NP. We also propose approximation algorithms for a special case, where each internal node has at most one recombination child and any two merge paths for different recombination nodes do not share any common node.
43310555
Twist-Rotation Transformations of Binary Trees and Arithmetic Expressions
The paper studies the computational complexity and efficient algorithms for the twist?rotation transformations of binary trees, which is equivalent to the transformation of arithmetic expressions over an associative and commutative binary operation. The main results are (1) a full binary tree with n labeled leaves can be transformed into any other in at most 3nlogn+2n twist and rotation operations, (2) deciding the twist?rotation distance between two binary trees is NP-complete, and (3) the twist?rotation transformation can be approximated with ratio 6logn+4 in polynomial time for full binary trees with n uniquely labeled leaves.
360687
Target-oriented scheduling in directional sensor networks
Unlike convectional omni-directional sensors that always have an omni-angle of sensing range, directional sensors may have a limited angle of sensing range due to technical constraints or cost considerations. A directional sensor network consists of a number of directional sensors, which can switch to several directions to extend their sensing ability to cover all the targets in a given area. Power conservation is still an important issue in such directional sensor networks. In this paper, we address the multiple directional cover sets problem (MDCS) of organizing the directions of sensors into a group of non-disjoint cover sets to extend the network lifetime. One cover set, in which the directions cover all the targets, is activated at one time. We prove the MDCS to be NP-complete and propose three heuristic algorithms for the MDCS. Simulation results are also presented to demonstrate the performance of these algorithms.
32144441
SmartBoa: Constructing p2p Overlay Network in the Heterogeneous Internet Using Irregular Routing Tables
The high heterogeneity of large-scale p2p system leads us to the philosophy that the size of a node’s routing table and its updating cost should correspond to the node’s capacity. With this philosophy, we design a novel structured overlay: SmartBoa. SmartBoa categorizes nodes into different levels according to their capacities. A node at level k has a routing table with N/2k entries (N is the system scale). An efficient non-redundant multicast algorithm is introduced to distribute nodes’ changing reports. With the multicast the routing table’s updating cost is in proportion to its size. Node can change its level freely so as to adapt to fluctuation of the system. At the same cost as the O(log N) overlay, SmartBoa maintains with much larger routing tables and has much higher routing efficiency. A low-bandwidth (64 kbps) node can maintain 10,000 routing entries at the cost of only 10 percent of its bandwidth. Without the high bandwidth requirement of an one-hop overlay, SmartBoa is much more scalable.