The auction algorithm: a distributed relaxation method for the assignment problem
Annals of Operations Research - Special Issue: Parallel Optimization on Novel Computer Architectures
Faster scaling algorithms for general graph matching problems
Journal of the ACM (JACM)
Network programming
Network flows: theory, algorithms, and applications
Network flows: theory, algorithms, and applications
Minkowski-type theorems and least-squares partitioning
SCG '92 Proceedings of the eighth annual symposium on Computational geometry
An efficient cost scaling algorithm for the assignment problem
Mathematical Programming: Series A and B
Introduction to Algorithms
IEEE Transactions on Computers
Optimization of AP Placement and Channel Assignment in Wireless LANs
LCN '02 Proceedings of the 27th Annual IEEE Conference on Local Computer Networks
Main Memory Evaluation of Monitoring Queries Over Moving Objects
Distributed and Parallel Databases
Centralized channel assignment and routing algorithms for multi-channel wireless mesh networks
ACM SIGMOBILE Mobile Computing and Communications Review
SINA: scalable incremental processing of continuous queries in spatio-temporal databases
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Monitoring k-Nearest Neighbor Queries over Moving Objects
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
SEA-CNN: Scalable Processing of Continuous K-Nearest Neighbor Queries in Spatio-temporal Databases
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Conceptual partitioning: an efficient method for continuous nearest neighbor monitoring
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
A Threshold-Based Algorithm for Continuous Monitoring of k Nearest Neighbors
IEEE Transactions on Knowledge and Data Engineering
Continuous Reverse Nearest Neighbor Monitoring
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
MobiEyes: A Distributed Location Monitoring Service Using Moving Location Queries
IEEE Transactions on Mobile Computing
Progressive computation of the min-dist optimal-location query
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
The Dynamic Assignment Problem
Transportation Science
Reverse nearest neighbor aggregates over data streams
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Capacity constrained assignment in spatial databases
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
On optimal worst-case matching
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
Optimal k-constraint coverage queries on spatial objects
ADC '12 Proceedings of the Twenty-Third Australasian Database Conference - Volume 124
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Consider a set of servers and a set of users, where each server has a coverage region (i.e., an area of service) and a capacity (i.e., a maximum number of users it can serve). Our task is to assign every user to one server subject to the coverage and capacity constraints. To offer the highest quality of service, we wish to minimize the average distance between users and their assigned server. This is an instance of a well-studied problem in operations research, termed optimal assignment. Even though there exist several solutions for the static case (where user locations are fixed), there is currently no method for dynamic settings. In this paper, we consider the continuous assignment problem (CAP), where an optimal assignment must be constantly maintained between mobile users and a set of servers. The fact that the users are mobile necessitates real-time reassignment so that the quality of service remains high (i.e., their distance from their assigned servers is minimized). The large scale and the time-critical nature of targeted applications require fast CAP solutions. We propose an algorithm that utilizes the geometric characteristics of the problem and significantly accelerates the initial assignment computation and its subsequent maintenance. Our method applies to different cost functions (e.g., average squared distance) and to any Minkowski distance metric (e.g., Euclidean, L 1 norm, etc.).