Distributed Data Placement and Content Delivery in Web Caches with Non-Metric Access Costs
Pages 4340 - 4351
Abstract
Motivated by applications in web caches and content delivery in peer-to-peer networks, we consider the non-metric data placement problem and develop distributed algorithms for computing or approximating its optimal solutions. In this problem, the goal is to store copies of the data points among a set of cache-capacitated servers to minimize overall data storage and clients' access costs. We first show that the non-metric data placement problem is inapproximable up to a logarithmic factor. We then provide a game-theoretic decomposition of the objective function and show that a natural type of Glauber dynamics in which servers update their cache contents with probability proportional to the utility they receive from caching those data will converge to an optimal global solution for a sufficiently large noise parameter. In particular, we establish the polynomial mixing time of the Glauber dynamics for a certain range of noise parameters. Such a game-theoretic decomposition not only provides a good performance guarantee in terms of content delivery but also allows the system to operate in a fully distributed manner, hence reducing its computational load and improving its robustness to failures. Moreover, we provide another auction-based distributed algorithm, which allows us to approximate the optimal solution with a performance guarantee that depends on the ratio of the revenue vs. social welfare obtained from the underlying auction.
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References
[1]
Karen Aardal, Fabian A. Chudak, and David B Shmoys. 1999. A 3-approximation algorithm for the ''-level uncapacitated facility location problem. Inform. Process. Lett. 72, 5--6 (1999), 161--167.
[2]
Eric Angel, Evripidis Bampis, Gerasimos G Pollatos, and Vassilis Zissimopoulos. 2014. Optimal data placement on networks with a constant number of clients. Theoretical Computer Science 540 (2014), 82--88.
[3]
Lazima Ansari. 2017. Large-scale Optimization for Data Placement Problem. University of Lethbridge (Canada).
[4]
Ivan Baev, Rajmohan Rajaraman, and Chaitanya Swamy. 2008. Approximation algorithms for data placement problems. SIAM J. Comput. 38, 4 (2008), 1411--1429.
[5]
Ivan D Baev and Rajmohan Rajaraman. 2001. Approximation algorithms for data placement in arbitrary networks. In Proceedings of the Twelfth Annual ACM-SIAM Symposium on Discrete Algorithms. 661--670.
[6]
Xuanyu Cao, Junshan Zhang, and H Vincent Poor. 2018. An optimal auction mechanism for mobile edge caching. In 2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS). IEEE, 388--399.
[7]
Moses Charikar, Sudipto Guha, Éva Tardos, and David B Shmoys. 1999. A constant-factor approximation algorithm for the ''-median problem. In Proceedings of the Thirty-First Annual ACM Symposium on Theory of Computing. 1--10.
[8]
Byung-Gon Chun, Kamalika Chaudhuri, Hoeteck Wee, Marco Barreno, Christos H Papadimitriou, and John Kubiatowicz. 2004. Selfish caching in distributed systems: A game-theoretic analysis. In Proceedings of the Twenty-Third Annual ACM Symposium on Principles of Distributed Computing. 21--30.
[9]
Shichuan Deng. 2022. Constant approximation for fault-tolerant median problems via iterative rounding. Operations Research Letters 50, 4 (2022), 384--390.
[10]
Maciej Drwal. 2013. Competitive algorithms for online data placement on uncapacitated uniform network. In Proceedings of the The Fifth International Conference on Advances in Future Internet. 1--7.
[11]
Maciej Drwal and Jerzy Jozefczyk. 2014. Decomposition algorithms for data placement problem based on Lagrangian relaxation and randomized rounding. Annals of Operations Research 222, 1 (2014), 261--277.
[12]
S. Rasoul Etesami. 2020. Complexity and Approximability of Optimal Resource Allocation and Nash Equilibrium over Networks. SIAM Journal on Optimization 30, 1 (2020), 885--914.
[13]
S. Rasoul Etesami and Tamer Ba?ar. 2016. Pure Nash equilibrium in a capacitated selfish resource allocation game. IEEE Transactions on Control of Network Systems 5, 1 (2016), 536--547.
[14]
S. Rasoul Etesami and Tamer Ba?ar. 2017. Price of anarchy and an approximation algorithm for the binary-preference capacitated selfish replication game. Automatica 76 (2017), 153--163.
[15]
Michel Goemans, Li Erran Li, Vahab S Mirrokni, and Marina Thottan. 2004. Market sharing games applied to content distribution in ad-hoc networks. In Proceedings of the 5th ACM International Symposium on Mobile Ad Hoc Networking and Computing. 55--66.
[16]
Ragavendran Gopalakrishnan, Dimitrios Kanoulas, Naga Naresh Karuturi, C Pandu Rangan, Rajmohan Rajaraman, and Ravi Sundaram. 2012. Cache me if you can: Capacitated selfish replication games. In Latin American Symposium on Theoretical Informatics. Springer, 420--432.
[17]
Minzhe Guo. 2016. Algorithmic Mechanism Design for Data Replication Problems. Ph.D. Dissertation. University of Cincinnati.
[18]
Dorit S Hochbaum. 1982. Heuristics for the fixed cost median problem. Mathematical Programming 22, 1 (1982), 148--162.
[19]
Huei-Chuen Huang and Rongheng Li. 2008. A ??-product uncapacitated facility location problem. European Journal of Operational Research 185, 2 (2008), 552--562.
[20]
Kamal Jain, Mohammad Mahdian, Evangelos Markakis, Amin Saberi, and Vijay V Vazirani. 2003. Greedy facility location algorithms analyzed using dual fitting with factor-revealing LP. Journal of the ACM (JACM) 50, 6 (2003), 795--824.
[21]
Prateek Jain, Dheeraj Nagaraj, and Praneeth Netrapalli. 2021. Making the last iterate of SGD information theoretically optimal. SIAM Journal on Optimization 31 (2021), 1108--1130.
[22]
Nathan Korda, Balazs Szorenyi, and Shuai Li. 2016. Distributed clustering of linear bandits in peer to peer networks. In International Conference on Machine Learning. PMLR, 1301--1309.
[23]
Ravishankar Krishnaswamy, Shi Li, and Sai Sandeep. 2018. Constant approximation for ??-median and ??-means with outliers via iterative rounding. In Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing. 646--659.
[24]
David A Levin and Yuval Peres. 2017. Markov Chains and Mixing Times. 2nd Ed. American Mathematical Soc.
[25]
Kanak Mahadik, Qingyun Wu, Shuai Li, and Amit Sabne. 2020. Fast distributed bandits for online recommendation systems. In Proceedings of the 34th ACM International Conference on Supercomputing. 1--13.
[26]
Igal Milchtaich. 1996. Congestion games with player-specific payoff functions. Games and Economic Behavior 13, 1 (1996), 111--124.
[27]
Dov Monderer and Lloyd S Shapley. 1996. Potential games. Games and Economic Behavior 14, 1 (1996), 124--143.
[28]
Valentino Pacifici and Gyorgy Dan. 2012. Convergence in player-specific graphical resource allocation games. IEEE Journal on Selected Areas in Communications 30, 11 (2012), 2190--2199.
[29]
Gerasimos G Pollatos, Orestis A Telelis, and Vassilis Zissimopoulos. 2008. On the social cost of distributed selfish content replication. In NETWORKING 2008 Ad Hoc and Sensor Networks, Wireless Networks, Next Generation Internet: 7th International IFIP-TC6 Networking Conference Singapore, May 5--9, 2008 Proceedings 7. Springer, 195--206.
[30]
Ohad Shamir and Tong Zhang. 2013. Stochastic gradient descent for non-smooth optimization: Convergence results and optimal averaging schemes. In International Conference on Machine Learning. PMLR, 71--79.
[31]
David B Shmoys, Éva Tardos, and Karen Aardal. 1997. Approximation algorithms for facility location problems. In Proceedings of the Twenty-ninth Annual ACM Symposium on Theory of Computing. 265--274.
[32]
Chaitanya Swamy. 2016. Improved approximation algorithms for matroid and knapsack median problems and applications. ACM Transactions on Algorithms (TALG) 12, 4 (2016), 1--22.
[33]
Sonika Thakral. 2017. Approximation Algorithms for Data Placement Problems. University of Delhi.
[34]
David P Williamson and David B Shmoys. 2011. The Design of Approximation Algorithms. Cambridge University Press.
Index Terms
- Distributed Data Placement and Content Delivery in Web Caches with Non-Metric Access Costs
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Published In
May 2024
4826 pages
ISBN:9798400701719
DOI:10.1145/3589334
- General Chairs:
- Tat-Seng Chua,
- Chong-Wah Ngo,
- Proceedings Chair:
- Roy Ka-Wei Lee,
- Program Chairs:
- Ravi Kumar,
- Hady W. Lauw
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Published: 13 May 2024
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