Caching in Wireless Multimedia Sensor Networks

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Caching in WirelessMultimedia Sensor Networks
_at_ Dept. of Computer Communication Engineering,
University of Thessaly _at_ Dept. of Informatics,
Aristotle University
Dimitrios Katsaros, Ph.D.
Lausanne, March 17th, 2008
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Outline of the talk

• A few words about my research
• Latest results
• Cooperative Caching in Wireless
• Multimedia Sensor Networks
• Appeared in MobiMedia Conf. 2007
• 2nd round review _at_ ACM Mobile Networks
  Applications
• PRIMITIVE Important Sensor Nodes
  Identification
• PROTOCOL Cooperative Caching
• GOAL Latency Reduction Uniform Energy
  Consumption

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My Research Areas (chronological info)

• WIRELESS NETWORKS
• Mobile Pervasive Computing
• Data Management
• Caching (04)
• Air-Indexing (07)
• Data Dissemination
• Broadcast Scheduling (04)
• Prediction
• Mobility Prediction (0308)
• Prefetching (03)
• Mobile Ad Hoc Networks
• Content-based Multimedia Retrieval (0508)
• Broadcasting (0608)
• Wireless Sensor Networks
• Sensor Network Clustering (07)
• (DistrLocal) Data Indexing (0608)
• Cooperative Caching (0708)
• Data Dissemination (08)

• WIRED NETWORKS
• Conventional and Streaming Media Distribution in
  the Web
• Replication (03)
• Prefetching (010203)
• Caching (04)
• Overlay and P2P Networks
• Content Distribution Networks (0506)
• Content Placement in CDNs (0708)
• Indexing Query Routing in P2P (progress)
• Distributed Structures over P2P (progress)
• Web Information Retrieval and Data Mining
• Web Link Mining (05)
• Web Ranking (0708)
• Rank Aggregation (0708)
• Social Network Analysis (0708)
• Bibliometrics (060708)

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Research areas Ultimately ? ???
Mobile/Pervasive Computing
Web
Sensor Web
Overlay Nets
Caching Air-Indexing
Content Distribution Networks
Caching Prefetching Replication
Semistructured Data
Web views
Webcasting
Location Tracking
Ad Hoc
Content-Based MIR
Broadcasting Data Dissemination
Web Ranking Search Engines
Cooperative Caching Sensor Node Clustering
Distributed Indexing Coverage/Connectivity
Flash storage
Social Network Analysis
Information Retrieval
Sensors
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In the sequel

• Wireless Sensor Networks
• Wireless Multimedia Sensor Networks
• Cooperative Caching
• Idea
• Relevant work
• Node-Importance Cooperative Caching protocol
• Which nodes are more important?
• Housekeeping information at NICoCa
• Cache Discovery Cache Replacement
• Evaluation

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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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Communication in WSNs

• Communication between two unconnected nodes is
  achieved through intermediate nodes
• Every node that falls inside the communication
  range r of a node u, is considered reachable
  (bidirectional links)

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WSNs - Applications

• Applications
• Habitat monitoring
• Disaster relief
• Target tracking
• Precision 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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WMSNs - Applications

• Boost the existing application of WSNs
• Create new applications
• multimedia surveillance sensor networks
  miniature video cameras that will communicate,
  process and store data relevant to crimes and
  terrorist attacks
• traffic avoidance and control systems will
  monitor car traffic and offer routing advices to
  prevent congestion
• industrial process control will be realized by
  WMSNs that will offer time-critical information
  related to imaging, temperature, pressure, etc

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Whats special about WMSNs ?

• Ian Akyildiz Dec06 Dec07 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

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Whats 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
• Although Jim Gray predicted that flash memories
  will replace hard disks

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Relevant work (1/2)

• Caching in OSs, DBMS, Web
• No extreme resource constraints
• Caching for wireless broadcast cellular networks
• more powerful nodes,
• one-hop communication with resource-rich base
  stations
• Most relevant research works
• cooperative caching protocols for MANETs
• GroCoca organize nodes into groups
• based on data request pattern mobility pattern)
• ECOR, Zone Co-operative, Cluster Cooperative
  form clusters of nodes
• based geographical proximity or adopting 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

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NICoCa consists of

• A metric for estimating the importance of a
  sensor node, which will imply short latency in
  retrieval
• A cooperative caching protocol which strives to
  achieve uniform energy consumption
• 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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Terminology and assumptions

• WMSN is abstracted as a graph G(V,E)
• edge e(u,v) exists iff u is in the transmission
  range of v and vice versa (bidirectional links)
• The network is assumed to be connected
• N1(v) the set of one hop neighbours of v
• N2(v) the set of two hop neighbours of v
• N12(v) combined set of N1(v) and N2(v)
• LNv is the induced subgraph of G associated
  with vertices in N12(v)
• dG(v,u) distance between v and u

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A measure of sensor importance

• suw swu number of shortest paths from u ? V to
  w ? V (suu0)
• suw(v) number of shortest paths from u to w
  that some vertex v ? V lies on
• Node importance index NI(v) of a vertex v is

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The NI index in sample graphs
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The NI index in sample graphs

• Nodes with large NI
• Articulation nodes (in bridges), e.g., 3, 4, 7,
  16, 18
• With large fanout, e.g., 14, 8, U

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Centralized solution ???

• Create a broadcast tree to coordinate the
  identification of NIs
• lot of messages
• larger latency
• Hot-spots in communication (nodes with large NI)
• Localized Algorithms are preferable
• NIs in neighborhoods

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The NI index in a localized algorithm
2-hop neighbors of node 8
node 8 calculates the NI of its 2-hop neighbors
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The NI index in a localized algorithm
nodes 14 and 16 are more important than the
others from the viewpoint of node 8
Each node can identify its own important nodes
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Housekeeping information in NICoCa

• Ultimate source of multimedia data Data Center
• Each node is aware of its 2-hop neighborhood
• Uses NI to characterize some neighbors as
  mediators
• Can be either a mediator or an ordinary node
• Each sensor node stores
• the dataID, and the actual datum
• the data size, TTL interval
• for each cached item
• characterized either as O (i.e., own) or H (i.e.,
  hosted)
• the timestamps of the K most recent accesses

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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
sparse WMSN (d 4)
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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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Observe MB files uniform access

• For all network topologies (sparse, dense and
  very dense), NICoCa achieves more remote hits and
  less global hits than HybridCache
• This performance gap widens in favor of NICoCa as
  we move from sparse to denser WMSNs
• For very dense sensor deployments, NICoCa
  achieves double the remote hits of HybridCache
  and only half of its global hits
• For sparse WMSNs HybridCache achieves slightly
  more local hits than does NICoCa, but this gap
  vanishes completely when moving to denser network
• This small gain of HybridCache for sparse
  topologies is not advantageous at all, since it
  incurs global hits as many as twice the number of
  its local hits

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Cache vs. hits (KB files Zipfian access) in a
sparse WMSN (d 4)
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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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Observe KB files Zipfian access

• For all network topologies (sparse, dense and
  very dense), NICoCa achieves more remote hits and
  less global hits than HybridCache
• For very dense WMSNs, the requests reaching Data
  Center for NICoCa are less than half those of
  HybridCache!
• NICoCa's global hits do not vary significantly
  with varying network topologies and varying local
  sensor storage
• Global hits of HybridCache are severely affected
  by the topology and the cache size
• For cache equal to 1 of the total data,
  HybridCache's global hits increase at a pace of
  50!
• The results for Zipfian access on megabyte-sized
  data more impressively in favor of NICoCa

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Summary

• Wireless Multimedia Sensor Networks (WMSNs)
• 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 references

1. I. Akyildiz, T. Melodia, and K. R. Chowdhury.
   Wireless multimedia sensor networks A survey.
   IEEE Wireless Communications magazine, 14(6), pp.
   32-39, Dec., 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?

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NI computation

• At a first glance, NI computation seems
  expensive, i.e., O(mn2) operations in total for
  a 2-hop neighbourhood, which consists of n nodes
  and m links
• calculating the shortest path between a
  particular pair of vertices (assume for the
  moment that there exists only one) can be done
  using bfs in O(m) time, and there exist O(n2)
  vertex pairs
• Fortunately, we can do better than this by making
  some smart observations. The improved algorithm
  (CalculateNodeImportanceIndex) is quite
  complicated and beyond the scope of this
  presentation
• THEOREM. The complexity of the algorithm
  CalculateNodeImportanceIndex is O(nm) for a
  graph with n vertices and m edges

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Pseudocode for CalculateNodeImportanceIndex (1/2)
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Pseudocode for CalculateNodeImportanceIndex (2/2)