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20
EnergyEfficient Algorithms for . . .
, 2007
"... We study scheduling problems in batteryoperated computing devices, aiming at schedules with low total energy consumption. While most of the previous work has focused on finding feasible schedules in deadlinebased settings, in this article we are interested in schedules that guarantee good respons ..."
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Cited by 70 (2 self)
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We study scheduling problems in batteryoperated computing devices, aiming at schedules with low total energy consumption. While most of the previous work has focused on finding feasible schedules in deadlinebased settings, in this article we are interested in schedules that guarantee good response times. More specifically, our goal is to schedule a sequence of jobs on a variablespeed processor so as to minimize the total cost consisting of the energy consumption and the total flow time of all jobs. We first show that when the amount of work, for any job, may take an arbitrary value, then no online algorithm can achieve a constant competitive ratio. Therefore, most of the article is concerned with unitsize jobs. We devise a deterministic constant competitive online algorithm and show that
Online scheduling
 Online Algorithms, Lecture Notes in Computer Science 1442
, 1998
"... Scheduling has been studied extensively in many varieties and from many viewpoints. Inspired by applications in practical computer systems, it developed into a theoretical area with many interesting results, both positive and negative. The basic situation we study is the following. We have some sequ ..."
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Cited by 33 (2 self)
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Scheduling has been studied extensively in many varieties and from many viewpoints. Inspired by applications in practical computer systems, it developed into a theoretical area with many interesting results, both positive and negative. The basic situation we study is the following. We have some sequence of jobs
A Combined BIT and TIMESTAMP Algorithm for the List Update Problem
 INFORMATION PROCESSING LETTERS
, 1995
"... We present a randomized online algorithm for the list update problem which achieves a competitive factor of 1.6, the best known so far. The algorithm makes an initial random choice between two known algorithms that have different worstcase request sequences. The first is the BIT algorithm that ..."
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Cited by 29 (11 self)
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We present a randomized online algorithm for the list update problem which achieves a competitive factor of 1.6, the best known so far. The algorithm makes an initial random choice between two known algorithms that have different worstcase request sequences. The first is the BIT algorithm that, for each item in the list, alternates between moving it to the front of the list and leaving it at its place after it has been requested. The second is a TIMESTAMP algorithm that moves an item in front of less often requested items within the list.
Base Station Scheduling of Requests with Fixed Deadlines
, 2002
"... We consider a packet switched wireless network in which a base station serves the mobiles. The packets for the mobiles arrive at the base station and have to be scheduled for transmission to the mobiles. The capacity of the channel from the base station to the mobiles is varying with time due to fad ..."
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Cited by 20 (0 self)
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We consider a packet switched wireless network in which a base station serves the mobiles. The packets for the mobiles arrive at the base station and have to be scheduled for transmission to the mobiles. The capacity of the channel from the base station to the mobiles is varying with time due to fading. We assume the mobiles can obtain different types of service based on the prices they are willing to pay. The objective of the base station is to schedule packets for transmission to mobiles to maximize the revenue earned. Our main result is that a simple greedy algorithm does at least # as good as the optimal offline algorithm that knows the complete future request pattern and channel conditions. We also show that no other online algorithm can do better.
SelfOrganizing Data Structures
 In
, 1998
"... . We survey results on selforganizing data structures for the search problem and concentrate on two very popular structures: the unsorted linear list, and the binary search tree. For the problem of maintaining unsorted lists, also known as the list update problem, we present results on the competit ..."
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Cited by 18 (0 self)
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. We survey results on selforganizing data structures for the search problem and concentrate on two very popular structures: the unsorted linear list, and the binary search tree. For the problem of maintaining unsorted lists, also known as the list update problem, we present results on the competitiveness achieved by deterministic and randomized online algorithms. For binary search trees, we present results for both online and offline algorithms. Selforganizing data structures can be used to build very effective data compression schemes. We summarize theoretical and experimental results. 1 Introduction This paper surveys results in the design and analysis of selforganizing data structures for the search problem. The general search problem in pointer data structures can be phrased as follows. The elements of a set are stored in a collection of nodes. Each node also contains O(1) pointers to other nodes and additional state data which can be used for navigation and selforganizati...
New Results for Online Page Replication
, 2003
"... We study the online page replication problem. We present a new randomized online algorithm for rings which is 2.37297competitive, improving the best previous result of 3.16396. We also show that no randomized online algorithm is better than 1.75037competitive on the ring; previously, only a 1.5819 ..."
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Cited by 6 (0 self)
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We study the online page replication problem. We present a new randomized online algorithm for rings which is 2.37297competitive, improving the best previous result of 3.16396. We also show that no randomized online algorithm is better than 1.75037competitive on the ring; previously, only a 1.58198 bound for a single edge was known. We extend the problem in several new directions: continuous metrics, variable size requests, and replication before service. This yields simplified proofs of several known results.
A New Lower Bound for the List Update Problem in the Partial Cost Model
, 1999
"... The optimal competitive ratio for a randomized online list update algorithm is known to be at least 1.5 and at most 1.6, but the remaining gap is not yet closed. We present a new lower bound of 1.50084 for the partial cost model. The construction is based on game trees with incomplete information, w ..."
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Cited by 4 (2 self)
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The optimal competitive ratio for a randomized online list update algorithm is known to be at least 1.5 and at most 1.6, but the remaining gap is not yet closed. We present a new lower bound of 1.50084 for the partial cost model. The construction is based on game trees with incomplete information, which seem to be generally useful for the competitive analysis of online algorithms.
Randomized Online Algorithms for the Buyback Problem
, 908
"... Abstract. In the matroid buyback problem, an algorithm observes a sequence of bids and must decide whether to accept each bid at the moment it arrives, subject to a matroid constraint on the set of accepted bids. Decisions to reject bids are irrevocable, whereas decisions to accept bids may be cance ..."
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Cited by 2 (0 self)
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Abstract. In the matroid buyback problem, an algorithm observes a sequence of bids and must decide whether to accept each bid at the moment it arrives, subject to a matroid constraint on the set of accepted bids. Decisions to reject bids are irrevocable, whereas decisions to accept bids may be canceled at a cost which is a fixed fraction of the bid value. We present a new randomized algorithm for this problem, and we prove matching upper and lower bounds to establish that the competitive ratio of this algorithm, against an oblivious adversary, is the best possible. We also observe that when the adversary is adaptive, no randomized algorithm can improve the competitive ratio of the optimal deterministic algorithm. Thus, our work completely resolves the question of what competitive ratios can be achieved by randomized algorithms for the matroid buyback problem. 1
A.: Distributed Computation Meets Design Theory: Local Scheduling for Disconnected Cooperation
 Bulletin of the EATCS
, 2004
"... y ..."
Page Migration with Limited Local Memory Capacity
 in Proc. of the 4th Workshop on Algorithms and Data Structures
, 1995
"... Page migration problems arise in distributed data management. The goal is to distribute a set of pages in a network of processors, each of which has its local memory, so that a sequence of memory accesses can be executed efficiently. Most previous work assumes that the local memories have infinite ..."
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Cited by 2 (0 self)
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Page migration problems arise in distributed data management. The goal is to distribute a set of pages in a network of processors, each of which has its local memory, so that a sequence of memory accesses can be executed efficiently. Most previous work assumes that the local memories have infinite capacities, which is unrealistic in practice. In this paper we study the migration problem under the assumption that the local memories have limited capacities. We assume that the memories are directmapped, i.e., the processors use a hash function in order to locate pages in their memory. We show that, for a number of important network topologies, online algorithms with a constant competitive ratio can be developed in this model. This is essentially the first work on page migration that makes realistic assumptions concerning memory capacity and develops upper bounds that are meaningful in practice. We also study distributed paging. We examine the migration version of this problem i...