A Lexicographic Optimization Algorithm

The increasing momentum of service-oriented architecture has led to the emergence of divergent delivered services, where service selection is meritedly required to obtain the target service fulfilling the requirements from both users and service providers. Despite many existing works have extensively handled the issue of service selection, it remains an open question in the case where requests from multiple users are performed simultaneously by a certain set of shared candidate services. Meanwhile, there exist some constraints enforced on the context of service selection, e.g. service placement location and contracts between users and service providers. In this paper, we focus on the QoS-aware service selection with constraints from a fairness aspect, with the objective of achieving max-min fairness across multiple service requests sharing candidate service sets. To be more specific, we study the problem of fairly selecting services from shared candidate sets while service providers are self-motivated to offer better services with higher QoS values. We formulate this problem as a lexicographical maximization problem, which is far from trivial to deal with practically due to its inherently multiobjective and discrete nature. A fairness-aware algorithm for concurrent service selection (FASS) is proposed, whose basic idea is to iteratively solve the single-objective subproblems by transforming them into linear programming problems. Experimental results based on real-world datasets also validate the effectiveness and practicality of our proposed approach.

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“…Jointly considering the linear relaxation on the integer constraints, the linear programming problem is eventually obtained as (21).…”

Section: B Lp Transformation Towards the Lowest Payment Maximizationmentioning

confidence: 99%

“…Besides, the optimal scheme obtained from the problem (17) also coincides with the one to the problem (10). To sum up, an optimal service selection scheme to the problem (21) is an optimal scheme to the problem (10).…”

Section: B Lp Transformation Towards the Lowest Payment Maximizationmentioning

confidence: 99%

FASS: A Fairness-Aware Approach for Concurrent Service Selection with Constraints

Huang

Cheng

et al. 2019

2019 IEEE International Conference on Web Services (ICWS)

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“…Based on the concept of the Tolerant Lexicographic Method [43] for multiobjective optimization, the solution can be determined as…”

Section: Local Optimization Based On Mc-icp For the Visual Mapmentioning

confidence: 99%

Visual Map Construction Using RGB-D Sensors for Image-Based Localization in Indoor Environments

Feng

Tan

2017

Journal of Sensors

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RGB-D sensors capture RGB images and depth images simultaneously, which makes it possible to acquire the depth information at pixel level. This paper focuses on the use of RGB-D sensors to construct a visual map which is an extended dense 3D map containing essential elements for image-based localization, such as poses of the database camera, visual features, and 3D structures of the building. Taking advantage of matched visual features and corresponding depth values, a novel local optimization algorithm is proposed to achieve point cloud registration and database camera pose estimation. Next, graph-based optimization is used to obtain the global consistency of the map. On the basis of the visual map, the image-based localization method is investigated, making use of the epipolar constraint. The performance of the visual map construction and the image-based localization are evaluated on typical indoor scenes. The simulation results show that the average position errors of the database camera and the query camera can be limited to within 0.2 meters and 0.9 meters, respectively.

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“…The dynamic packet classifier receives the data packets from the neighbour node or the upper layers then classifies them into one of the four aforementioned categories, and forwards them to their respective module on a First-Come-First-Serve (FCFS) basis. The energy-aware geographic forwarding module decides the next hop node with least distance and comparatively high residual energy using multi-objective Lexicographic Optimization (LO) discussed in [27].…”

Section: B New Qos and Geographic Routing (Localmor)mentioning

confidence: 99%

A Comprehensive Survey of QoS-Aware Routing Protocols in Wireless Body Area Networks

M¹,

Raj²

2017

International Journal of Advanced Research in Computer and Comm

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Recent developments in wireless communications, MicroElectroMechanical Systems (MEMS) technology and integrated circuits have enabled low-power, intelligent, miniaturized, invasive/non-invasive micro sensor nodes strategically placed in or around the human body which forms Wireless Body Area Networks (WBANS) to be used in various applications including remote health monitoring. Due to inherent issues and specific challenges, routing protocols designed for Mobile Adhoc Networks (MANETs) and Wireless Sensor Networks (WSNs) are not applicable to WBANs. QoS-Aware Routing protocols mainly provide a modular approach by presenting separate modules for different QoS metrics that operate in coordination with each other. These approaches aim at providing higher reliability, lower end-to-end delay and higher packet delivery ratio. In this paper various issues and challenges in pursuit of effective QoS-Aware routing are identified and detailed literature survey of the various existing QoS-aware routing protocols, their strengths and weaknesses are discussed.

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A Lexicographic Optimization Algorithm

Cited by 37 publications

References 0 publications

FASS: A Fairness-Aware Approach for Concurrent Service Selection with Constraints

FASS: A Fairness-Aware Approach for Concurrent Service Selection with Constraints

Visual Map Construction Using RGB-D Sensors for Image-Based Localization in Indoor Environments

A Comprehensive Survey of QoS-Aware Routing Protocols in Wireless Body Area Networks

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