IDEAS home Printed from https://ideas.repec.org/a/spr/infosf/v11y2009i5d10.1007_s10796-008-9123-2.html
   My bibliography  Save this article

A novel memory management scheme for residential gateways

Author

Listed:
  • Ibrahim Kamel

    (University of Sharjah)

  • Beizhong Chen

    (Rutgers University)

Abstract

Home gateways must manage services despite limited memory resources. In home gateway models (e.g., OSGi), services are implemented as software bundles (or plug-ins) that can be downloaded from the Internet and executed in the gateway. Services, in gateways, are not independent; they collaborate and complement each other. The problem we are solving is as follow: when the gateway runs out of memory, which service(s) will be stopped or kicked out of memory to start a new service? The problem was initially inspired by the FTTH (Fibre To The Home) trail project in Japan with NTT because of the limited memory in Panasonic set-top-box IP-STB. Note that stopping a given service means that all the services that depend on it will be stopped too. Because of the service dependencies, traditional memory management techniques, such as best fit, first fit, or worst fit, are not suitable. Our goal is to minimize the total number of stopped services while fulfilling the request of the new service. In this paper, we present two algorithms for service replacement and memory management in home gateways. The algorithms take into consideration the dependencies between different services, in addition to the amount of memory occupied by each service. The first one achieves optimal solution in O(n 2) time and O(nh) space, using dynamic programming. However, the optimal solution requires substantial memory and CPU resources. Then we propose a heuristic that compute solutions very close to the optimal but with much less time and space requirements. We carry simulation experiments to evaluate the effectiveness of the proposed techniques and compare them with traditional memory management techniques.

Suggested Citation

  • Ibrahim Kamel & Beizhong Chen, 2009. "A novel memory management scheme for residential gateways," Information Systems Frontiers, Springer, vol. 11(5), pages 491-500, November.
    • Handle: RePEc:spr:infosf:v:11:y:2009:i:5:d:10.1007_s10796-008-9123-2
    DOI: 10.1007/s10796-008-9123-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10796-008-9123-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10796-008-9123-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. D. S. Johnson & K. A. Niemi, 1983. "On Knapsacks, Partitions, and a New Dynamic Programming Technique for Trees," Mathematics of Operations Research, INFORMS, vol. 8(1), pages 1-14, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. van der Merwe, D.J. & Hattingh, J.M., 2006. "Tree knapsack approaches for local access network design," European Journal of Operational Research, Elsevier, vol. 174(3), pages 1968-1978, November.
    2. N. Samphaiboon & Y. Yamada, 2000. "Heuristic and Exact Algorithms for the Precedence-Constrained Knapsack Problem," Journal of Optimization Theory and Applications, Springer, vol. 105(3), pages 659-676, June.
    3. Sofie Coene & Frits C. R. Spieksma & Gerhard J. Woeginger, 2011. "Charlemagne's Challenge: The Periodic Latency Problem," Operations Research, INFORMS, vol. 59(3), pages 674-683, June.
    4. Egor Ianovski, 2022. "Electing a committee with dominance constraints," Annals of Operations Research, Springer, vol. 318(2), pages 985-1000, November.
    5. van de Leensel, R.L.J.M. & Flippo, O.E. & Koster, Arie M.C.A. & Kolen, A.W.J., 1996. "A dynamic programming algorithm for the local access network expansion problem," Research Memorandum 027, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    6. Santiago Valdés Ravelo, 2022. "Approximation algorithms for simple assembly line balancing problems," Journal of Combinatorial Optimization, Springer, vol. 43(2), pages 432-443, March.
    7. You, Byungjun & Yamada, Takeo, 2007. "A pegging approach to the precedence-constrained knapsack problem," European Journal of Operational Research, Elsevier, vol. 183(2), pages 618-632, December.
    8. W. Lambert & A. Newman, 2014. "Tailored Lagrangian Relaxation for the open pit block sequencing problem," Annals of Operations Research, Springer, vol. 222(1), pages 419-438, November.
    9. Daniel Espinoza & Marcos Goycoolea & Eduardo Moreno & Alexandra Newman, 2013. "MineLib: a library of open pit mining problems," Annals of Operations Research, Springer, vol. 206(1), pages 93-114, July.
    10. Kameshwaran, S. & Narahari, Y. & Rosa, Charles H. & Kulkarni, Devadatta M. & Tew, Jeffrey D., 2007. "Multiattribute electronic procurement using goal programming," European Journal of Operational Research, Elsevier, vol. 179(2), pages 518-536, June.
    11. Frank Gurski & Dominique Komander & Carolin Rehs, 2020. "Solutions for subset sum problems with special digraph constraints," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 92(2), pages 401-433, October.
    12. Aslan, Ayse & Ursavas, Evrim & Romeijnders, Ward, 2023. "A Precedence Constrained Knapsack Problem with Uncertain Item Weights for Personalized Learning Systems," Omega, Elsevier, vol. 115(C).
    13. Kameshwaran, S. & Narahari, Y., 2009. "Nonconvex piecewise linear knapsack problems," European Journal of Operational Research, Elsevier, vol. 192(1), pages 56-68, January.
    14. Steffen Goebbels & Frank Gurski & Dominique Komander, 2022. "The knapsack problem with special neighbor constraints," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 95(1), pages 1-34, February.
    15. Flippo, Olaf E. & Kolen, Antoon W. J. & Koster, Arie M. C. A. & van de Leensel, Robert L. M. J., 2000. "A dynamic programming algorithm for the local access telecommunication network expansion problem," European Journal of Operational Research, Elsevier, vol. 127(1), pages 189-202, November.
    16. Heungsoon Felix Lee & Daniel R. Dooly, 1996. "Algorithms for the constrained maximum‐weight connected graph problem," Naval Research Logistics (NRL), John Wiley & Sons, vol. 43(7), pages 985-1008, October.
    17. Safer, Hershel M. & Orlin, James B., 1953-, 1995. "Fast approximation schemes for multi-criteria flow, knapsack, and scheduling problems," Working papers 3757-95., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    18. Xu, Liang & Xu, Zhou & Xu, Dongsheng, 2013. "Exact and approximation algorithms for the min–max k-traveling salesmen problem on a tree," European Journal of Operational Research, Elsevier, vol. 227(2), pages 284-292.
    19. Laurent Gourvès & Jérôme Monnot & Lydia Tlilane, 2018. "Subset sum problems with digraph constraints," Journal of Combinatorial Optimization, Springer, vol. 36(3), pages 937-964, October.
    20. Pinker, Edieal & Szmerekovsky, Joseph & Tilson, Vera, 2014. "On the complexity of project scheduling to minimize exposed time," European Journal of Operational Research, Elsevier, vol. 237(2), pages 448-453.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:infosf:v:11:y:2009:i:5:d:10.1007_s10796-008-9123-2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.