Papers by Mangesh Gharote
2023 IEEE/ACM 23rd International Symposium on Cluster, Cloud and Internet Computing Workshops (CCGridW)
2023 IEEE/ACM 23rd International Symposium on Cluster, Cloud and Internet Computing Workshops (CCGridW)
2022 IEEE/ACM 15th International Conference on Utility and Cloud Computing (UCC)
2017 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)
Stable Matching (SM) has received a lot of attention from researchers due to its useful applicati... more Stable Matching (SM) has received a lot of attention from researchers due to its useful applications in practice. Gale and Shapley were the first to propose a polynomial-time algorithm to find an SM solution, for matching with strict preferences. However, their algorithm often produces extreme stable solutions, favouring either men or women. In practice, the real-life problems have multiple objectives (equitable and welfare) and preferences are not strict, consequently ties occur. With the inclusion of ties and objectives, the problem becomes NP-hard. A few researchers proposed local search and evolutionary algorithms to solve multi-objective SM problem with ties, but these methods were not scalable. In this paper, we propose an efficient Goal Programming and Repair Heuristics based approach to solve this problem. On comparison with other related works, our approach shows significant improvement in respective objectives (equity and welfare). This approach with slight modification can be proved useful for solving other hard variants of the SM problem.
Queue
Each online interaction with an external service creates data about the user that is digitally re... more Each online interaction with an external service creates data about the user that is digitally recorded and stored. These external services may be credit card transactions, medical consultations, census data collection, voter registration, etc. Although the data is ostensibly collected to provide citizens with better services, the privacy of the individual is inevitably put at risk. With the growing reach of the Internet and the volume of data being generated, data protection and, specifically, preserving the privacy of individuals, have become particularly important. In this article we discuss the data privacy concepts using two fictitious characters, Swara and Betaal, and their interactions with a fictitious entity, namely Asha Hospital.
Proceedings of the 12th International Conference on Cloud Computing and Services Science
2020 IEEE International Conference on Services Computing (SCC)
Service organizations need to comply with numerous data regulations to protect and preserve their... more Service organizations need to comply with numerous data regulations to protect and preserve their customers’ privacy. Any misuse of data and privacy breach can affect the organizations’ reputation and brand image. In service delivery scenarios, such as IT support help desk, agents need to access customer data to serve them effectively. This data often includes sensitive and personally identifiable information of the customer. While some amount of data exposure is needed to serve a customer, however, exposure to more data than required could be a threat to an individual’s privacy. Hence, organizations need to design methodologies to ensure customer privacy while achieving minimal cost of operations.In this paper, we propose the Privacy Enabled Task Allocation (PETA) model for assigning customer requests to agents so that the overall cost of operations and data exposure is minimal. Data exposure is minimized by restricting the amount of data exposure per agent and by regulating the assignment of tasks. The PETA problem is modelled as an integer linear program, which is NP-hard. To solve this combinatorial hard problem, we have designed an allocation algorithm based on the linear programming relaxation for finding a quick feasible solution.
International Conference on Management of Data, Dec 14, 2012
Ordering queries within a workload and ordering joins in a query are important problems in databa... more Ordering queries within a workload and ordering joins in a query are important problems in databases [1]. We give algorithms for the query sequencing problem that scale (small space) and are efficient (low runtime) as compared to earlier work [4]. The errors are small in practice and we are able to further reduce them using geometric repair. We provide a computational comparison of TSP solvers and show extensive testing on benchmark datasets [25] observing its connection to these ordering problems.
P u b l i c a ti o n o f A C M I n d i a Each online interaction with an external service creates... more P u b l i c a ti o n o f A C M I n d i a Each online interaction with an external service creates data about the user that is digitally recorded and stored. These external services may be credit card transactions, medical consultations, census data collection, voter registration, etc. Although the data is ostensibly collected to provide citizens with better services, privacy of the individual is inevitably put at risk. With the growing reach of the internet and the volume of data being generated, data protection and, specifically, preserving the privacy of individuals, have become particularly important. This Minigraph gives an overview of privacy. We discuss how privacy has evolved over time. The privacy concepts are discussed using two fictitious characters, Swara and Betaal, and their interactions with a fictitious entity, namely Asha Hospital. An introduction to privacy and associated concerns (Sections 1 and 2) is followed by descriptions of two important privacy preserving techniques, k-anonymity (Section 3) and differential privacy (Section 4). Lastly, some new approaches to ensuring privacy are discussed (Section 5).
The determination of threshold is a complex and a time consuming task. Existing threshold value r... more The determination of threshold is a complex and a time consuming task. Existing threshold value recommendation approaches are either not generalizable or requires further improvement in accuracy. In this paper, we propose an approach that computes two properties namely, symmetric and transitive, on the confidence values computed by an ontology matching algorithm in order to recommend the threshold. We demonstrate the effectiveness of our solution through experiments by comparing our solution with the hierarchical agglomerative clustering.
CSI Transactions on ICT, 2022
Enterprises are availing the benefits of cloud computing in terms of distributed resources, quick... more Enterprises are availing the benefits of cloud computing in terms of distributed resources, quick deployment, cost effectiveness, scalability, uninterrupted services and hence, are hosting services on cloud. However, these services require transfer of customer data across borders which could violate local, national, or international regulations or even could lead to unintended access of data. Data Residency (DaR) is one such regulation that deals with the location and movement of data across geographies and jurisdictions, and protection against unintended access. Data regulations are enforced by countries. Some countries have stringent regulations, while some have conditional regulations. These regulations could vary according to the data type. Hence, each organization operating in multi-geographies and serving customers across the borders needs to comply with DaR regulations. In this work, we present a model-driven framework that aims to provide decision support for the enterprise to assist in selection of cloud data centers for hosting web-services and placement of customer data, such that they are DaR complaint.
The performance of ontology matching algorithms is evaluated using F-measure, precision and recal... more The performance of ontology matching algorithms is evaluated using F-measure, precision and recall which in turn rely on the availability of the ground truth. Typically, the ground truth generation process is manual, subjective and time consuming. Therefore, there is a need to come up with a (semi) automated approach which generates an unbiased reference set; an approximation of ground truth. We propose a framework based solution to generate a reference set and report encouraging results for the OAEI 2019 conference dataset.
We have proposed a novel approach for campus interview panel formation, selection and candidate m... more We have proposed a novel approach for campus interview panel formation, selection and candidate matching process. In practice, interview panel selection has been a judgemental task, performed manually by an experienced manager. The challenge is in identifying suitable interviewers from a large set of possible experts, forming panels and matching them to the candidates’ profile. We have captured the rules and methodology used by the manager for this recruitment process in the integer linear programming formulation with probabilistic constraints. The solution would be effective for organizations which recruit in bulk and on regular basis, to recruit the right talent.
2016 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), 2016
In this paper, we address the problem of allocating workforce to software projects, considering b... more In this paper, we address the problem of allocating workforce to software projects, considering bilateral (project managers' and employees') preferences and cost of allocation. Earlier research has addressed the workforce allocation to software projects as stable matching problem with strict preferences ranking. However, in practice, there are scenarios where project managers did not strictly rank the employees; therefore, there are ties in the preference list. We developed a stable matching with ties-based optimization model to create a minimum cost stable allocation. Our results suggest that a software firm can reduce allocation cost and improve the average preferences for both the workforce and the project managers in the presence of ties in the preference list.
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2021
The appropriate choice of locations for the deployment of web services is of significant importan... more The appropriate choice of locations for the deployment of web services is of significant importance. The placement of a web service closer to user centers minimizes the response time, however deployment cost may increase. The placement becomes more challenging when multiple web services are involved. In this paper, we address the problem of placing multiple web services with the aim of simultaneously minimizing conflicting objectives of total deployment cost and network latency. We solve the location allocation problem for each web service independently and combine the resulting solutions using a novel merge algorithm. We demonstrate through extensive experiments and simulations that the proposed approach is not only computationally efficient but also produces good quality solutions. Further, the proposed merge algorithm is generic and could be easily adapted to tackle any bi-objective optimization problem that can be decomposed into non-overlapping sub-problems.
2020 IEEE International Conference on Services Computing (SCC), 2020
With the evolving data regulations and residency laws, it is becoming challenging for enterprises... more With the evolving data regulations and residency laws, it is becoming challenging for enterprises to serve all the geographically distributed users. To abide with the regulations and to leverage the benefits, such as good quality of service at a low cost, and avoid vendor lock-in, enterprises are seeking multiple Cloud Service Providers (CSPs) for hosting their web applications. The selection of CSPs in a multi-cloud environment is a challenging problem as it depends on multiple criteria such as security, service cost, manageability and so on.In this paper, we address the CSP selection problem for multiple applications in a multi-cloud environment comprising of multiple criteria. We provide a holistic solution methodology that ranks the CSP combinations for each web application using a multiple-criteria decision-making (MCDM) technique. The solution methodology takes virtual machine and cloud center selection into consideration for ranking the CSP combinations. However, selecting the top ranked CSP combinations for all applications may not be a viable option from the manageability and budget perspectives. Hence, we propose an optimization model to select CSPs for multiple applications of an enterprise considering budget and rank. We demonstrate our methodology through numerical experiments and provide various insights.
Journal of Heuristics, 2017
In this paper, we study a centralized, stable matching scheme, which allocates trainees to softwa... more In this paper, we study a centralized, stable matching scheme, which allocates trainees to software project requirements, to minimize retraining and relocation costs when the preference lists of the project requirements may contain ties of arbitrary lengths. This particular trainees’ assignment problem is important because the allocation decisions not only influence the costs but also impact software project deliverables and intern attrition rates. It is also an NP-hard problem because of the inclusion of the ties, and the costs in the stable allocation model. We, therefore, have designed a GRASP-based scatter search method, to solve the large size instances of our assignment problem efficiently. The GRASP method uses randomized algorithms to generate initial trial solutions. A repair heuristic based on regret minimization idea is designed to convert an unstable solution to a stable solution during an improvement phase. Computational experiments suggest that the proposed algorithm significantly reduces run time compared to the CPLEX, and produces solutions that are at an average 4.5% away from the best CPLEX solutions for the large size problem instances. Moreover, our scatter search method consistently provides better quality solutions than the two state of the art methods from the prior literature.
2015 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), 2015
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Papers by Mangesh Gharote