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15
Modeling and assessing inference exposure in encrypted databases
 ACM Transactions on Information and System Security (TISSEC
, 2005
"... The scope and character of today’s computing environments are progressively shifting from traditional, oneonone clientserver interaction to the new cooperative paradigm. It then becomes of primary importance to provide means of protecting the secrecy of the information, while guaranteeing its ava ..."
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Cited by 49 (25 self)
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The scope and character of today’s computing environments are progressively shifting from traditional, oneonone clientserver interaction to the new cooperative paradigm. It then becomes of primary importance to provide means of protecting the secrecy of the information, while guaranteeing its availability to legitimate clients. Operating online querying services securely on open networks is very difficult; therefore many enterprises outsource their data center operations to external application service providers. A promising direction toward prevention of unauthorized access to outsourced data is represented by encryption. However, data encryption is often supported for the sole purpose of protecting the data in storage while allowing access to plaintext values by the server, which decrypts data for query execution. In this paper, we present a simple yet robust singleserver solution for remote querying of encrypted databases on external servers. Our approach is based on the use of indexing information attached to the encrypted database, which can be used by the server to select the data to be This paper extends the previous work by the authors appeared under the title “Balancing
A 3/4Approximation Algorithm for Multiple Subset Sum
 Journal of Heuristics
, 2003
"... The Multiple Subset Sum Problem (MSSP) is the variant of bin packing in which the number of bins is given and one would like to maximize the overall weight of the items packed in the bins. The problem is also a special case of the multiple knapsack problem in which all knapsacks have the same cap ..."
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Cited by 10 (0 self)
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The Multiple Subset Sum Problem (MSSP) is the variant of bin packing in which the number of bins is given and one would like to maximize the overall weight of the items packed in the bins. The problem is also a special case of the multiple knapsack problem in which all knapsacks have the same capacity and the item prots and weights coincide.
Approximation Algorithms for Scheduling with Reservations
"... Abstract. We study the problem of scheduling n independent jobs on a system of m identical parallel machines in the presence of reservations. This constraint is practically important; for various reasons, some machines are not available during specified time intervals. The objective is to minimize t ..."
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Cited by 9 (4 self)
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Abstract. We study the problem of scheduling n independent jobs on a system of m identical parallel machines in the presence of reservations. This constraint is practically important; for various reasons, some machines are not available during specified time intervals. The objective is to minimize the makespan. This problem is inapproximable in the general case unless P = NP which motivates the study of suitable restrictions. We use an approach based on algorithms for multiple subset sum problems; our technique yields a polynomial time approximation scheme (PTAS) which is best possible in the sense that the problem does not admit an FPTAS unless P = NP. The PTAS presented here is the first one for the problem under consideration; so far, not even for special cases approximation schemes have been proposed. We also derive a low cost algorithm with a constant approximation ratio and discuss additional FPTASes for special cases and complexity results. 1
A survey on approximation algorithms for scheduling with machine unavailability
 In Algorithmics of Large and Complex Networks: Design, Analysis, and Simulation
, 2009
"... Abstract. In this chapter we present recent contributions in the field of sequential job scheduling on network machines which work in parallel; these are subject to temporary unavailability. This unavailability can be either unforeseeable (online models) or known a priori (offline models). For the o ..."
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Abstract. In this chapter we present recent contributions in the field of sequential job scheduling on network machines which work in parallel; these are subject to temporary unavailability. This unavailability can be either unforeseeable (online models) or known a priori (offline models). For the online models we are mainly interested in preemptive schedules for problem formulations where the machine unavailability is given by a probabilistic model; objectives of interest here are the sum of completion times and the makespan. Here, the nonpreemptive case is essentially intractable. For the offline models we are interested in nonpreemptive schedules where we consider the makespan objective; we present approximation algorithms which are complemented by suitable inapproximability results. Here, the preemptive model is polynomialtime solvable for large classes of settings. 1
Network delayaware load balancing in selfish and cooperative distributed systems
 CoRR
"... Abstract—We consider a geographically distributed request processing system composed of various organizations and their servers connected by the Internet. The latency a user observes is a sum of communication delays and the time needed to handle the request on a server. The handling time depends on ..."
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Abstract—We consider a geographically distributed request processing system composed of various organizations and their servers connected by the Internet. The latency a user observes is a sum of communication delays and the time needed to handle the request on a server. The handling time depends on the server congestion, i.e. the total number of requests a server must handle. We analyze the problem of balancing the load in a network of servers in order to minimize the total observed latency. We consider both cooperative and selfish organizations (each organization aiming to minimize the latency of the locallyproduced requests). The problem can be generalized to the task scheduling in a distributed cloud; or to content delivery in an organizationallydistributed CDNs. In a cooperative network, we show that the problem is polynomially solvable. We also present a distributed algorithm iteratively balancing the load. We show how to estimate the distance between the current solution and the optimum based on the amount of load exchanged by the algorithm. During the experimental evaluation, we show that the distributed algorithm is efficient, therefore it can be used in networks with dynamically changing loads. In a network of selfish organizations, we prove that the price of anarchy (the worstcase loss of performance due to selfishness) is low when the network is homogeneous and the servers are loaded (the request handling time is high compared to the communication delay). After relaxing these assumptions, we assess the loss of performance caused by the selfishness experimentally, showing that it remains low. Our results indicate that a set of servers handling requests, connected in a heterogeneous network, can be efficiently managed by a distributed algorithm. Additionally, even if the network is organizationally distributed, with individual organizations optimizing performance of their requests, the network remains efficient. I.
Faster Approximation Algorithms for Scheduling with Fixed Jobs
"... We study the problem of scheduling jobs on identical parallel machines without preemption. In the considered setting, some of the jobs are already assigned machines and starting times, for example due to external constraints not explicitly modelled. The objective is to assign the rest of the jobs in ..."
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We study the problem of scheduling jobs on identical parallel machines without preemption. In the considered setting, some of the jobs are already assigned machines and starting times, for example due to external constraints not explicitly modelled. The objective is to assign the rest of the jobs in order to minimize the makespan. It is known that this problem cannot be approximated better than within a factor of 3/2 unless P = NP. An algorithm that achieves 3/2 + ɛ for any ɛ> 0 was presented by Diedrich and Jansen [DJ09], but its running time is doubly exponential in 1/ɛ. We present an improved algorithm with approximation ratio 3/2 and polynomial running time. We also give matching results for the related problem of scheduling with reservations. The new algorithm is both faster and conceptually simpler than the previously known algorithms. 1
Rod cutting optimization with store utilization
 In International design conference
, 2000
"... rod cutting, bin packing problem, multiple subset sum problem Abstract: For cutting linear elements like steel rod or marble shelf from standard lengths, optimization for best utilization of raw material is frequently required to minimize waste and reduce the production costs with packing smaller e ..."
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rod cutting, bin packing problem, multiple subset sum problem Abstract: For cutting linear elements like steel rod or marble shelf from standard lengths, optimization for best utilization of raw material is frequently required to minimize waste and reduce the production costs with packing smaller elements to standard lengths. As the input material can be order dependent, store handling is limited only to good remnants from previous cuttings or overstocking. To handle production of this type rationally, solution consist of several types of optimizations. Putting theory to work in real production demands several aspects of application to be considered to fit the needs of designers and orders staff. 1
Coupledtasks in presence of bipartite compatibilities graphs
"... Abstract. We tackle the makespan minimization coupledtasks problem in presence of incompatibility constraints. In particular, we focus on stretched coupledtasks, i.e.coupledtasks having the same subtasks execution time and idle time duration. We study several problems in the framework of classi ..."
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Abstract. We tackle the makespan minimization coupledtasks problem in presence of incompatibility constraints. In particular, we focus on stretched coupledtasks, i.e.coupledtasks having the same subtasks execution time and idle time duration. We study several problems in the framework of classic complexity and approximation for which the compatibility graph is bipartite (star, chain,...). In such context, we design efficient polynomialtime approximation algorithms according to different parameters of the scheduling problem. 1
Scheduling coupledtasks with incompatibility constraint: a binpacking related problem
"... Abstract. We tackle the makespan minimization problem of coupledtasks in presence of compatibility constraint. In particular, we focus on stretched coupledtasks, i.e. coupledtasks having the same subtasks execution time and idle time duration. We show the relationship with bin packing problems f ..."
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Abstract. We tackle the makespan minimization problem of coupledtasks in presence of compatibility constraint. In particular, we focus on stretched coupledtasks, i.e. coupledtasks having the same subtasks execution time and idle time duration. We show the relationship with bin packing problems for some configurations, and study several problems in framework of complexity and approximation for which the topology of the compatibility graph is specific (star, chain, bipartite,...). 1
Makespan Minimization with Machine Availability Constraints
"... Abstract. We investigate the problems of scheduling n jobs to m = m1 + m2 identical machines where m1 machines are always available, m2 machines have some specified unavailable intervals. The objective is to minimize the makespan. We assume that if a job is interrupted by the unavailable interval, i ..."
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Abstract. We investigate the problems of scheduling n jobs to m = m1 + m2 identical machines where m1 machines are always available, m2 machines have some specified unavailable intervals. The objective is to minimize the makespan. We assume that if a job is interrupted by the unavailable interval, it can be resumed after the machine becomes available. We show that if at least one machine is always available, i.e. m1> 0, then the PTAS for Multiple Subset Sum problem given by Kellerer [3] can be applied to get a PTAS; otherwise, m = m2, every machine has some unavailable intervals, we show that if (m − 1) machines each of which has unavailable intervals with total length bounded by α(n)·Psum/m where Psum is the total processing time of all jobs and α(n) can be any nonnegative function, we can develop a (1 + α(n) +ɛ)−approximation algorithm for any constant 0 <ɛ<1; finally we show that there does not exist any polynomial time (1 + α(n) − o(1))−approximation unless P=NP.