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© University of Fribourg, Switzerland 1
Chapter 18: Energy-efficient Peer-to-Peer
Networking and Overlays
1Apostolos Malatras, 1Fei Peng, and 1Béat Hirsbrunner
1University 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
© University of Fribourg, Switzerland 2
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
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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 it’s 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
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Introduction
Motivation Growing need for energy proportional computing
approaches• Energy consumption proportional to operation and Energy consumption proportional to operation and
performanceperformance
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 Need to address end hosts (peers), overlay networks and
communication protocolscommunication protocols
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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
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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
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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
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Examples of P2P Overlays
Structured Unstructured
Chord Freenet
Tapestry Gnutella
Pastry FastTrack/Kazaa
Kademlia BitTorrent
Viceroy UMM
CAN Newscast
Cycloid Phenix
SkipNet BlatAnt
P-Grid
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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
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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
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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, Studies in [Ou et al., 2009, 2010], [Kassinen et al., 2008,
2009], 2009],
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Taxonomy of energy-efficient P2P approaches
Category Examples
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]
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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?
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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
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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 Has been measured to be up to 64% of overall energy
consumptionconsumption
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
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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
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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 Additionally, ensures proper operation of the P2P overlay because energy depletion implies the node will go because energy depletion implies the node will go permanently offlinepermanently offline
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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 Constraints include battery lifetime, processing load, data
transfer rates, etc.transfer rates, etc.
How to model energy consumption is a difficult problem
• Task allocation requires some level of prediction regarding the Task allocation requires some level of prediction regarding the expected energy consumption to decide whether re-allocation expected energy consumption to decide whether re-allocation of a task makes sense or notof a task makes sense or not
Selfish behavior of peers• Selfless behavior has been shown to extend the overall P2P Selfless behavior has been shown to extend the overall P2P
overlay lifetimeoverlay lifetime
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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 This selfish behavior can have adverse effect on the proper operation of the P2P overlay [Feldman & Chuang, 2005]operation of the P2P overlay [Feldman & Chuang, 2005]
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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
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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
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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 don’t 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
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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
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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 Queries are quickly directed to the nodes who can satisfy
themthem
Similar concept as geographic routing
Challenges Acquiring location information Sharing location information in distributed settings Privacy issues
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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
© University of Fribourg, Switzerland 26
Thanks for your attention!