1. © University of Fribourg, Switzerland1 Chapter 18: Energy-efficient Peer-to-Peer Networking and Overlays 1 Apostolos Malatras, 1 Fei Peng, and 1 Béat Hirsbrunner 1 University of Fribourg, Switzerland HANDBOOK ON GREEN INFORMATION AND COMMUNICATION SYSTEMS The work presented here was conducted in the context of SNF-funded BioMPE project, grant number 200021_130132

2. © University of Fribourg, Switzerland2 Outline Introduction Motivation P2P Systems Energy profile of P2P Systems Taxonomy of energy-efficient P2P approaches Proxying Sleep-and-Wake Task allocation optimization Message reduction Overlay structure optimization Location-based Conclusions

3. © University of Fribourg, Switzerland3 Introduction Peer-to-peer paradigm has gained wide acceptance over the last years Allows for more manageable networks due to its nature as networking abstraction layer Information Technology is a large consumer of energy resources Recent surveys indicate its responsible for up to 3% of global energy consumption Rapidly increasing due to wide deployment of IT devices and exponential growth of networks (wired and wireless) P2P network traffic has been measured to be from 40% to 73% of the overall Internet traffic

4. © University of Fribourg, Switzerland4 Introduction Motivation Growing need for energy proportional computing approaches Energy consumption proportional to operation and performanceEnergy consumption proportional to operation and performance A lot of potential in overall IT energy savings from energy-efficient P2P approaches Challenges Distributed nature of P2PDistributed nature of P2P Need to address end hosts (peers), overlay networks and communication protocolsNeed to address end hosts (peers), overlay networks and communication protocols

5. © University of Fribourg, Switzerland5 Terminology & Focus Terms used interchangeably P2P systems P2P overlays P2P networks Focus of study Work with experimental or testbed validation Not dealing with MANETs Similar concept, but different OSI layerSimilar concept, but different OSI layer Energy-efficient research work and P2P systems that are targeted at extending lifetime of mobile devices

6. © University of Fribourg, Switzerland6 What is a P2P Overlay? A logical, virtual network that is built upon a real, physical network The peers, i.e. nodes in the physical network, are organized in a distributed manner Peer organization adheres to specific criteria/rules All peers are operating as both clients and servers Its goal is to support a variety of services and applications Hide complexity, heterogeneity and dynamicity of underlying networking infrastructures Promote scalability

7. © University of Fribourg, Switzerland7 Structured vs. Unstructured P2P Structured P2P Topology is tightly controlled Rules about placement of resources on specific peers Usually exploit Distributed Hash TablesUsually exploit Distributed Hash Tables Quick discovery of resources High maintenance and management overhead costs Unstructured P2P No rules to control topology Flexible membership and resource positioning Flooding used to locate resources More flexible and resilient to failures More effort/time required to locate resources

8. © University of Fribourg, Switzerland8 Examples of P2P Overlays StructuredUnstructured ChordFreenet TapestryGnutella PastryFastTrack/Kazaa KademliaBitTorrent ViceroyUMM CANNewscast CycloidPhenix SkipNetBlatAnt P-Grid

9. © University of Fribourg, Switzerland9 Energy profile of P2P systems Important to know how much energy P2P systems consume and on what operations Accurate measurements can validate the potential reductions in energy consumption Selection of strategy to follow, e.g. promoting modifications in energy consuming operations Energy models can be a good alternative Give a quick indication of energy behaviorsGive a quick indication of energy behaviors Allow for early validation experiments/analysisAllow for early validation experiments/analysis Shorter rollout times for new, green P2PShorter rollout times for new, green P2P Standard metrics are lacking, hence no reliable comparisons between different P2P can be drawn

10. © University of Fribourg, Switzerland10 Energy profile of P2P systems Energy model described in [Nedevschi et al., 2008] Comparison of P2P with centralized solutions End-to-end analysis of energy behaviors P2P are greener when considering only end-hosts Centralized are greener in the end-to-end case Energy model by [Hlavacs et al., 2010, 2011] Focus on BitTorrent and peer participation Relation between optimal time to actively participate in the BitTorrent P2P and the optimal energy efficiency Energy model by [Zhang & Helvik, 2010] Models amount of time peers stay actively in the P2P network vs. consumed energy

11. © University of Fribourg, Switzerland11 Energy profile of P2P systems Viability of mobile devices participating in a P2P network studied in [Zhuang et al., 2010] Possible but at a high battery cost as shown in [Gurun et al., 2006], [Rollins et al., 2011] P2P energy efficiency in wired vs. wireless networks has been studied Different behavior due to wireless medium characteristics was observed in [Gerla et al., 2005] Feasible operation, works better when high data transfer rates can be ensured Studies in [Ou et al., 2009, 2010], [Kassinen et al., 2008, 2009],Studies in [Ou et al., 2009, 2010], [Kassinen et al., 2008, 2009],

12. © University of Fribourg, Switzerland12 Taxonomy of energy-efficient P2P approaches CategoryExamples Proxying[Agarwal et al., 2009], [Kelenyi et al., 2009], [Kelenyi et al., 2010], [Anastasi et al., 2010], [Purushothaman at al., 2006] Sleep-and-Wake[Sucevic et al., 2009], [Gurun et al., 2006], [Blackburn & Christensen, 2009] Task allocation optimization[Aikebaier et al., 2009], [Enokido et al., 2010], [Li et al., 2009] Message reduction[Kelenyi et al., 2008], [da Hora et al., 2007], [Kelenyi et al., 2010] Overlay structure optimization[Leung & Kwok, 2008], [Han et al., 2008], [Choi &Woo, 2006], [Rollins et al., 2011], [Mawji et al., 2011], [Macedo et al., 2011] Location-based[Park & Valduriez, 2011], [Tung & Lin, 2011], [Joseph et al. 2005], [Feng et al., 2007]

13. © University of Fribourg, Switzerland13 Proxying Use of proxies by P2P hosts to delegate P2P- related activities and operations and thus allow to have more idle time. Peers can then go on sleep mode, consuming less energy Overall P2P system energy consumption is reduced Challenges Which P2P operations to offload to the proxy? When to wake up the P2P host? Where should the proxy be located? Since participation to the P2P has to be active, e.g. file sharing, how can this be accommodated with a proxy?

14. © University of Fribourg, Switzerland14 Proxying Solutions proposed in the literature 1 proxy for many peers Proxy consumes energy as wellProxy consumes energy as well Offloaded P2P operations AllAll SelectiveSelective Proxy location Wireless gatewaysWireless gateways NIC of hostNIC of host Dedicated machinesDedicated machines Host wake up Completion of file downloadCompletion of file download Threshold for number of downloaded pieces (e.g. BitTorrent)Threshold for number of downloaded pieces (e.g. BitTorrent) P2P operation Proxy acts as full delegate for the P2P hosts it servesProxy acts as full delegate for the P2P hosts it serves Peers are still part of the P2P network, but passive membersPeers are still part of the P2P network, but passive members

15. © University of Fribourg, Switzerland15 Sleep-and-Wake P2P hosts adopt and adaptive operational behavior by selectively switching between on and off state in order to save energy Motivation lies in the energy requirements of wireless interfaces Has been measured to be up to 64% of overall energy consumptionHas been measured to be up to 64% of overall energy consumption Random switching on and off is harmful for P2P operation Specially designed scheduling is required As soon as downloads have been completedAs soon as downloads have been completed Be active only when high data rates can be guaranteedBe active only when high data rates can be guaranteed Buffer all requests and handled them when going onlineBuffer all requests and handled them when going online

16. © University of Fribourg, Switzerland16 Sleep-and-Wake Challenges Proper operation of the P2P network is hindered because of high peer churn When buffering requests, efficiency of the P2P network is diminished, e.g. longer delays Connectivity of the P2P overlay cannot be guaranteed due to peer churn Most proposed solutions require global network information to properly schedule sleeping and waking times Unviable assumption that cannot be applied in real settingsUnviable assumption that cannot be applied in real settings

17. © University of Fribourg, Switzerland17 Task allocation optimization Scheduling of tasks across P2P hosts in a manner that limits overall energy consumption by utilizing host availability more efficiently Considers the P2P overlay similarly to a grid system Not all hosts have the same energy capacity/capability The more processing a peer does and the more information it transfers/receives, the more energy it consumes Scheduling ensures a fair consumption of energy among participating peers Additionally, ensures proper operation of the P2P overlay because energy depletion implies the node will go permanently offlineAdditionally, ensures proper operation of the P2P overlay because energy depletion implies the node will go permanently offline

18. © University of Fribourg, Switzerland18 Task allocation optimization Challenges Task allocation optimization requires global knowledge about the status of peers in the P2P network All related work is modeled as multi-constraint optimization problem Constraints include battery lifetime, processing load, data transfer rates, etc.Constraints include battery lifetime, processing load, data transfer rates, etc. How to model energy consumption is a difficult problem Task allocation requires some level of prediction regarding the expected energy consumption to decide whether re-allocation of a task makes sense or notTask allocation requires some level of prediction regarding the expected energy consumption to decide whether re-allocation of a task makes sense or not Selfish behavior of peers Selfless behavior has been shown to extend the overall P2P overlay lifetimeSelfless behavior has been shown to extend the overall P2P overlay lifetime

19. © University of Fribourg, Switzerland19 Message reduction Technique used to reduce number of messages. By minimizing the number of sent messages, processing and transmission times are reduced and thus energy is conserved Both for wired and wireless networks Wired: less processingWired: less processing Wireless: less transmissions/receptionsWireless: less transmissions/receptions Studies validated that peers that act only as clients have less power consumption that full-fledged ones [Kelenyi et al., 1008] This selfish behavior can have adverse effect on the proper operation of the P2P overlay [Feldman & Chuang, 2005]This selfish behavior can have adverse effect on the proper operation of the P2P overlay [Feldman & Chuang, 2005]

20. © University of Fribourg, Switzerland20 Message reduction Benefits In [Kelenyi et al., 2008] it was shown that with a 50% drop probability the consumed energy was reduced by 55% Challenges Dropping of messages Selective, e.g. not management messagesSelective, e.g. not management messages RandomRandom Ensuring proper operation of the P2P overlay Replication of messagesReplication of messages Replication of resourcesReplication of resources Not all peers dropping messagesNot all peers dropping messages

21. © University of Fribourg, Switzerland21 Overlay structure optimization New topology designs for energy efficient P2P overlays or modifications to existing ones to satisfy energy requirements Existing popular P2P systems do not take into account energy resources for construction and maintenance Main reason was the abundance of mains power in wired devices Nowadays, wireless devices are the norm and designs need to be reconsidered Such omission can quickly deplete energy-constrained devices and thus compromise the viability of the P2P overlay as a whole

22. © University of Fribourg, Switzerland22 Overlay structure optimization Solution proposed by [Leung & Kwok, 2008] Peers decide on who their neighbors will be based on their remaining battery levels Nodes who dont have a lot of battery will be leaf nodes, while relay nodes have high energy capacity Promotes P2P overlay longevity Super peer approaches Building maximal independent set of most energy- powerful peers Information relaying happens through this set of super peers Adaptive approaches needed to ensure super peer energy does not get drained quickly

23. © University of Fribourg, Switzerland23 Location-based Location-information is used to make P2P overlays more closely matching their physical underlay counterparts, thus reducing multi-hop transmissions Mostly useful for wireless networks One overlay hop can be multiple physical layer hops, so many retransmissions might be needed for a single message When overlay and underlay match each other closely, less retransmissions are likely to occur and thus less energy is to be consumed Some overlay structure optimization approaches can be classified in this category

24. © University of Fribourg, Switzerland24 Location-based Location-based resource discovery greatly benefits from such approaches When location is taken into account to construct the P2P overlay, this information is always available Resource queries for spatial data can then be satisfied much quicker and in a more energy efficient manner Queries are quickly directed to the nodes who can satisfy themQueries are quickly directed to the nodes who can satisfy them Similar concept as geographic routing Challenges Acquiring location information Sharing location information in distributed settings Privacy issues

25. © University of Fribourg, Switzerland25 Conclusions Survey of green P2P Scholar overview of existing solutions Highlight pitfalls and challenges Promote novel solutions by cross-examination Future directions to engage in green P2P Need for standard metrics that will lead to comparable measurements Accurate and reliable models of energy efficiency of P2P systems End-to-end solutions, i.e. not only considering end hosts but also the energy footprint of the core and that of communications

26. © University of Fribourg, Switzerland26 Thanks for your attention!