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1 Cooperative Caching in Wireless Multimedia Sensor Nets Nikos Dimokas 1 Dimitrios Katsaros 1,2 (presentation) Yannis Manolopoulos 1 3 rd MobiMedia Conference, Nafpaktos, Greece, 27- 29/August/2007 1 Informatics Dept., Aristotle University, Thessaloniki, Greece 2 Computer & Communication Engin. Dept., University of Thessaly, Volos, Greece

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Cooperative Caching in Wireless Multimedia Sensor Nets. Nikos Dimokas 1 Dimitrios Katsaros 1,2 (presentation) Yannis Manolopoulos 1. 1 Informatics Dept., Aristotle University, Thessaloniki, Greece 2 Computer & Communication Engin. Dept., University of Thessaly, Volos, Greece. - PowerPoint PPT Presentation

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Page 1: Cooperative Caching in  Wireless Multimedia Sensor Nets

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Cooperative Caching in Wireless Multimedia Sensor Nets

Nikos Dimokas1

Dimitrios Katsaros1,2 (presentation)Yannis Manolopoulos1

3rd MobiMedia Conference, Nafpaktos, Greece, 27-29/August/2007

1Informatics Dept., Aristotle University, Thessaloniki, Greece2Computer & Communication Engin. Dept., University of Thessaly, Volos, Greece

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Wireless Sensor Networks (WSNs)

Wireless Sensor Networks features

• Homogeneous devices• Stationary nodes• Dispersed network• Large network size• Self-organized• All nodes acts as routers• No wired infrastructure• Potential multihop routes

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WSNs - Applications• Applications

• Habitat monitoring• Disaster relief• Target tracking• Agriculture

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Wireless Multimedia Sensor Nets (WMSNs)

Cheap CMOS cameras: Cyclops imaging module is a light-weight imaging module which can be adapted to MICA2 or MICAz sensor nodes

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What’s so special about WMSNs ?• [Ian Akyildiz: Dec’06] We have to rethink the

computation-communication paradigm of traditional WSNs• which focused only on reducing energy consumption

• WMSNs applications have a second goal, as important as the energy consumption • delivery of application-level quality of service (QoS) • mapping of this requirement to network layer metrics,

like latency• This goal has (almost) been ignored in

mainstream research efforts on traditional WSNs

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What’s so special about WMSNs ?• Resource constraints

• sensor nodes are battery-, memory- and processing-starving devices

• Variable channel capacity• multi-hop nature of WMSNs implies that wireless

link capacity depends on the interference level among nodes

• Multimedia in-network processing• sensor nodes store rich media (image, video),

and must retrieve such media from remote sensor nodes with short latency

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Our proposal …

• Cooperative Caching: NICOCA protocol• multiple sensor nodes share and coordinate cache

data to cut communication cost and exploit the aggregate cache space of cooperating sensors

• Each sensor node has a moderate local storage capacity associated with it, i.e., a flash memory

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Relevant work (1/2)• Caching in operating systems, in databases, on

the Web • No extreme resource constraints like WMSNs

• Caching for wireless broadcast cellular networks • More powerful nodes, and one-hop communication

with resource-rich base stations• Most relevant research works:

• cooperative caching protocols for MANETs• GroCoca: organize nodes into groups based on their data

request pattern and their mobility pattern• ECOR, Zone Co-operative, Cluster Cooperative: form

clusters of nodes based either in geographical proximity or utilizing widely known node clustering algorithms for MANETs

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Relevant work (2/2)Protocols that deviated from such approaches:• CacheData: intermediate nodes cache the

data to serve future requests instead of fetching data from their source

• CachePath: mobile nodes cache the data path and use it to redirect future requests to the nearby node which has the data instead of the faraway origin node

• Amalgamation of them: the champion HybridCache cooperative caching for MANETs

• One caching work on WSNs• concerns the placement of caches

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Our contributions …

• Definition of a metric for estimating the importance of a sensor node, which will imply short latency in retrieval

• Description of a cooperative caching protocol which takes into account the residual energy

• Datum discovery and cache replacement component subprotocols

• Performance evaluation of the protocol and comparison with the state-of-the-art cooperative caching for MANETs, with J-Sim

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A measure of sensor importance• Let σuw=σwu denote the number of shortest paths

from u V to w V (by definition, σuu=0)• Let σuw(v) denote the number of shortest paths from

u to w that some vertex v V lies on• We define the node importance index NI(v) of a

vertex v as:

• Large values for the NI index of a node v indicate that this node can reach others on relatively short paths, or that v lies on considerable fractions of shortest paths connecting others

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The NI index in sample graphsIn parenthesis, the NI index of the respective node; i.e., 7(156): node with ID 7 has NI equal to 156.

Nodes with large NI:

Articulation nodes (in bridges), e.g., 3, 4, 7, 16, 18

With large fanout, e.g., 14, 8, U

Therefore: geodesic nodes

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The cache discovery protocol (1/2)A sensor node issues a request for a

multimedia item• Searches its local cache and if it is found (local

cache hit) then the K most recent access timestamps are updated

• Otherwise (local cache miss), the request is broadcasted and received by the mediators

• These check the 2-hop neighbors of the requesting node whether they cache the datum (proximity hit)

• If none of them responds (proximity cache miss), then the request is directed to the Data Center

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The cache discovery protocol (2/2)When a mediator receives a request, searches

its cache• If it deduces that the request can be satisfied by a

neighboring node (remote cache hit), forwards the request to the neighboring node with the largest residual energy

• If the request can not be satisfied by this mediator node, then it does not forward it recursively to its own mediators, since this will be done by the routing protocol, e.g., AODV

• If none of the nodes can help, then requested datum is served by the Data Center (global hit )

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The cache replacement protocol• Each sensor node first purges the data that it has cached

on behalf of some other node• Calculate the following function for each cached datum i

• The candidate cache victim is the item which incurs the largest cost

• Inform the mediators about the candidate victim• If it is cached by a mediator, the metadata are updated• If not, it is forwarded and cached to the node with the

largest residual energy

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Evaluation setting (1/2)• We compared NICOCA to:

• Hybrid, state-of-the-art cooperative caching protocol for MANETs

• Implementation of protocols using J-Sim simulation library

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Evaluation setting (2/2)• Measured quantities

• number of hits (local, remote and global)• residual energy level of the sensor nodes• average latency for getting the requested data• the number of packets dropped

• Present here only results for number of hits• representative of: latency, collisions and energy consumption

• A small number of global hits• less network congestion, fewer collisions and packet drops.

• Large number of remote hits effectiveness of cooperation

• Large number of local hits ≠ effective cooperation• the cost of global hits vanishes the benefits of local hits

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Cache vs. hits (MB files & uniform access) in a dense WMSN (d = 7)

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Cache vs. hits (MB files & uniform access) in a very dense WMSN (d = 10)

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Cache vs. hits (KB files & Zipfian access) in a dense WMSN (d = 7)

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Cache vs. hits (KB files & Zipfian access) in a very dense WMSN (d = 10)

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Summary• Wireless Multimedia Sensor Networks (WMSNs)• Unique features of WMSNs call for protocol

designs that provide application-level QoS• Cooperative caching protocol, NICoCa, suitable

for WMSNs• NICOCA evaluation with J-Sim and comparison

to the state-of-the-art protocol• NICOCA can:

• reduce the global hits at an average percentage of 50%

• increase the remote hits (due to the effective sensor cooperation) at an average percentage of 40%

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Important references1. I. Akyildiz, T. Melodia, and K. R. Chowdhury. A survey

of wireless multimedia sensor networks. Computer Networks, 51:921-960, 2007

2. Y. Diao, D. Ganesan, G. Mathur, and P. Shenoy. Rethinking data management for storage-centric sensor networks. Proceedings of the Conference on Innovative Data Systems Research (CIDR), pp. 22-31, 2007

3. S. Nath and A. Kansal. FlashDB: Dynamic self-tuning database for NAND flash. Proceedings of the ACM International Conference on Information Processing in Sensor Networks (IPSN), pp. 410-419, 2007

4. L. Yin and G. Cao. Supporting cooperative caching in ad hoc networks. IEEE Transactions on Mobile Computing, 5(1):77-89, 2006

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Thank you for your

attention!

Any questions?