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Resource Augmenting Technological
"... This paper constructs a threesector growth model with nonrenewable environmental resource and a resource augmenting technological progress, and investigates the relation between the sustainability of resource use and growth of the nations. When the resource augmenting technological progress arises ..."
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This paper constructs a threesector growth model with nonrenewable environmental resource and a resource augmenting technological progress, and investigates the relation between the sustainability of resource use and growth of the nations. When the resource augmenting technological progress
Resource Augmentation in Load Balancing
 Algorithm Theory  SWAT 2000, 7th Scandinavian Workshop on Algorithm Theory, Proceedings, volume 1851 of Lecture Notes in Computer Science
, 2000
"... We consider load balancing in the following setting. The online algorithm is allowed to use n machines, whereas the optimal oline algorithm is limited to m machines, for some xed m < n. We show that while the greedy algorithm has a competitive ratio which decays linearly in the inverse of n ..."
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Cited by 5 (2 self)
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We consider load balancing in the following setting. The online algorithm is allowed to use n machines, whereas the optimal oline algorithm is limited to m machines, for some xed m < n. We show that while the greedy algorithm has a competitive ratio which decays linearly in the inverse of n=m, the best online algorithm has a ratio which decays exponentially in n=m. Specically, we give a deterministic algorithm with competitive ratio of 1 + 2 n m (1 o(1)) , and a lower bound of 1 + e n m (1+o(1)) on the competitive ratio of any randomized algorithm. We also consider the preemptive case. We show an online algorithm with a competitive ratio of 1 + e n m (1+o(1)) . We show that the algorithm is optimal by proving a matching lower bound. We also consider the nonpreemptive model with temporary tasks. We prove that for n = m + 1, the greedy algorithm is optimal. (It is not optimal for permanent tasks.) A preliminary version of this paper appears in the proceedings of the 7th Biennial Scandinavian Workshop on Algorithm Theory, SWAT 2000. y Dept. of Computer Science, TelAviv University. EMail: azar@math.tau.ac.il. Research supported in part by the Israel Science Foundation and by the United StatesIsrael Binational Science Foundation (BSF). z Dept. of Computer Science, TelAviv University. EMail: lea@math.tau.ac.il. Part of the research was done while this author was visiting the Centre for Mathematics and Computer Science (CWI), supported by a grant from the Netherlands Organization of Scientic Research. x Centre for Mathematics and Computer Science (CWI). EMail: Rob.van.Stee@cwi.nl. Research supported by the Netherlands Organization for Scientic Research (NWO), project number SION 61230002. 1 1
Optimal timecritical scheduling via resource augmentation.
 In Proc. of the 29th ACM Symposium on Theory of Computing,
, 1997
"... Abstract We consider two fundamental problems in dynamic scheduling: scheduling to meet deadlines in a preemptive multiprocessor setting, and scheduling to provide good response time in a number of scheduling environments. When viewed from the perspective of traditional worstcase analysis, no good ..."
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Cited by 158 (6 self)
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, no good online algorithms exist for these problems, and for some variants no good offline algorithms exist unless P = "P. We study these problems using a relaxed notion of competitive analysis, introduced by Kalyanasundaram and Pruhs, in which the online algorithm is allowed more resources than
Optimal resource augmentations for online knapsack
 IN APPROXRANDOM (2007
, 2007
"... It is known that online knapsack is not competitive. This negative result remains true even if the items are removable. In this paper we consider online removable knapsack with resource augmentation, in which we hold a knapsack of capacity R ≥ 1.0 and aim at maintaining a feasible packing to maximiz ..."
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Cited by 3 (0 self)
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It is known that online knapsack is not competitive. This negative result remains true even if the items are removable. In this paper we consider online removable knapsack with resource augmentation, in which we hold a knapsack of capacity R ≥ 1.0 and aim at maintaining a feasible packing
Online bin packing with resource augmentation
 IN PROCEEDINGS OF THE 2ND WORKSHOP ON APPROXIMATION AND ONLINE ALGORITHMS (WAOA 2004
, 2004
"... In competitive analysis, we usually do not put any restrictions on the computational complexity of online algorithms, although efficient algorithms are preferred. Thus if such an algorithm were given the entire input in advance, it could give an optimal solution (in exponential time). Instead of giv ..."
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Cited by 17 (3 self)
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In competitive analysis, we usually do not put any restrictions on the computational complexity of online algorithms, although efficient algorithms are preferred. Thus if such an algorithm were given the entire input in advance, it could give an optimal solution (in exponential time). Instead of giving the algorithm more knowledge about the input, in this paper we consider the effects of giving an online bin packing algorithm larger bins than the offline algorithm it is compared to. We give new algorithms for this problem that combine items in bins in an unusual way and give bounds on their performance which improve upon the best possible bounded space algorithm. We also give general lower bounds for this problem which are nearly matching for bin sizes b ≥ 2.
Optimal online flow time with resource augmentation
 IN PROC. 13TH SYMP. FUND. COMP. THEORY, NUMBER 2138 IN LNCS
, 2001
"... We study the problem of scheduling n jobs that arrive over time. We consider a nonpreemptive setting on a single machine. The goal is to minimize the total flow time. We use extra resource competitive analysis: an optimal offline algorithm which schedules jobs on a single machine is compared to a ..."
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Cited by 3 (0 self)
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for a hard version of the problem where the sizes of the smallest and the largest jobs are not known in advance, only ∆ and n are known. This gives a tradeoff between the resource augmentation and the competitive ratio. We also consider scheduling on parallel identical machines. In this case
Online Tree Node Assignment with Resource Augmentation
"... Abstract. Given a complete binary tree of height h,theonline tree node assignment problem is to serve a sequence of assignment/release requests, where an assignment request, withanintegerparameter0 ≤ i ≤ h, is served by assigning a (tree) node at level (or height) i and a release request is served b ..."
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Cited by 1 (0 self)
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results focus on how to achieve good performance when the same amount of resource is given to both the online and the optimal offline algorithms, i.e., one tree. In this paper, we focus on resource augmentation, where the online algorithm is allowed to use more trees than the optimal offline algorithm
RESOURCE AUGMENTATION FOR PERFORMANCE GUARANTEES IN EMBEDDED REALTIME SYSTEMS RESOURCE AUGMENTATION FOR PERFORMANCE GUARANTEES IN EMBEDDED REALTIME SYSTEMS
"... Abstract Realtime scheduling policies have been widely studied, with many known schedulability and feasibility analysis techniques for different task models, that have advanced the stateoftheart. Most of these techniques are typically derived under the assumption of negligible runtime overheads ..."
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resource augmentation, viz., processor speedup, to guarantee desired realtime properties even under the presence of runtime overheads. We specifically consider preemptions and faults that, at runtime, manifest as overheads in the system in various ways. Our aim is to provide specified non
Mixedcriticality scheduling: improved resourceaugmentation results
 In Proceedings of the ICSA International Conference on Computers and their Applications (CATA). IEEE
, 2010
"... Many safetycritical embedded systems are subject to certification requirements; some systems may be required to meet multiple sets of certification requirements, from different certification authorities. Certification requirements in such “mixedcriticality” systems give rise to some interesting ..."
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Cited by 10 (5 self)
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Many safetycritical embedded systems are subject to certification requirements; some systems may be required to meet multiple sets of certification requirements, from different certification authorities. Certification requirements in such “mixedcriticality” systems give rise to some interesting scheduling problems, that cannot be satisfactorily addressed using techniques from conventional scheduling theory. It had previously been shown that determining whether a system specified in this model can be scheduled to meet all its certification requirements is highly intractable. Prior work [4] had also introduced a simple, prioritybased scheduling algorithm called OCBP for mixed criticality systems, and had quantified, via the metric of processor speedup factor, the effectiveness of OCBP in scheduling dualcriticality systems – systems subject to two sets of certification requirements. In this paper, we extend this result to systems with arbitrarily many distinct criticality levels, by deriving a quantitative processor speedup factor (that depends on n) for OCBP when scheduling systems with n criticality levels for arbitrary n. 1
Multiprocessor Scheduling to Minimize Flow Time with ε Resource Augmentation
 IN PROC. 36TH SYMP. THEORY OF COMPUTING (STOC)
, 2004
"... We investigate the problem of online scheduling of jobs to minimize flow time and stretch on m identical machines. We consider the case where the algorithm is given either (1 + ε)m machines or m machines of speed (1 + ε), for arbitrarily small ε>0. We show that simple randomized and deterministic ..."
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Cited by 43 (3 self)
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ratios for flow time or stretch with arbitrarily small resource augmentation. Both the randomized and the deterministic load balancing algorithms are nonmigratory and do immediate dispatch of jobs. The randomized
Results 1  10
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