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8/14/2019 Wireless Grid
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Wireless Grids - Amin Ghadersohi 1
Wireless Grids
Amin Ghadersohi
Department of Computer Science and Engineering, SUNY-Buffalo,
NY.
4/4/2005
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Overview
Introduction
What is the Grid?
What is Grid Computing?
Wireless Grids
Motives and Driving Forces
Infrastructure
Performance
Hybrid Grid Project Proposal
Grid Examples
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Introduction
I think there is a world market for maybe 5computers. Thomas Watson (IBM), 1943
Computers in the future may weigh no more than1.5 tons. Popular Mechanics, 1949
Data Processing is a fad that wont last out theyear. Business Book Editor Prentice Hall, 1957
There is no reason anyone would want a computer
in their home. Ken Olsen (President DEC), 1977 640K ought to be enough for anybody. -Bill Gates,
1981
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What is the Grid?
Grids have moved from the obscurely academic to
the highly popular. Compute Grids, Data Grids, Science Grids, Access
Grids, Knowledge Grids, Bio Grids, Sensor Grids,Cluster Grids, Campus Grids, Tera Grids, and
Commodity Grids. So what exactly is the Grid?
a funding conceptand, as industry becomes
involved, a marketing slogan. The word Grid is chosen by analogy with the electric
power grid.
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What is the Grid?
A Three Point Grid Checklist*
1. Coordination of resources that are not subject tocentralized control;
2. Use of standard, open, general-purpose protocols
and interfaces; and3. Delivery of nontrivial qualities of service.
The end user does not have to know or care wherethe computing is performed or the data stored.
*I. Foster, What is the Grid? A Three Point Checklist, Argonne National Laboratory,http://www- fp.mcs.anl.gov/~foster/Articles/WhatIsTheGrid.pdf, 2002.
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What is the Grid?
Characteristics of current Grid system
Large-scale Heterogeneous
Dynamic resource sharing relationship
Service Oriented/Policy Driven
The essence of Grid Technology is
virtualization, the ability to abstract thephysical datacenter into a set of logicalcomponents.
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Wireless Grids
The emergence of the Wireless Grid meets
all these criteria and is fueled bytechnological advances in two major areas:
Grid Computing
Wireless Technology Pros and Cons
Pros: ubiquity, availability, productivity
Cons: constraints of wireless network Unpredictable network quality Lowered trust and robustness
Limited local resources and battery lifetime for mobile devices
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What is Grid Computing?
Distributed, high performance computing and
data handling infrastructure that: Incorporates geographically and organizationally
dispersed, heterogeneous resources (computing
systems, storage systems, instruments, and otherreal-time data sources, human collaborators, and
communication systems)
Provides common interfaces for allresources.
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Grid Architecture
Open Grid Services Architecture (OGSA)
Virtual Organization (VO): a set of individuals or institutionsthat provide or request resources.
Service orientation: everything is service.
Service virtualization: definition separated from
implementation. Service semantics -- the Grid Service: standard interfaces of
interoperability
Discovery: service data, service registration, service data retrieving
Dynamic service creation: service factory Lifetime management: service destroy and termination, keep alive
Notification
Ian Foster, Carl Kesselman, Jeffrey M. Nick, Steven Tuecke, "The Physiology of the Grid: An OpenGrid Services Architecture for Distributed Systems Integration." Open Grid Service InfrastructureWG, Global Grid Forum, June 2002.
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Related Technologies Cluster computing
Primarily concerned with a collection of homogeneous computational
resources. Physically bound.
Could be a grid node.
CORBA CORBA was a precursor to the Web (grid) services world we live in today.
Foundation for Java Remote Method Invocation (RMI)
DCE DCE (Distributed Computing Environment) is not so much an architecture as
it is an environment.
Facilitate distributed computing.
P2P
E.g.: KaZaA Lacks a central point of management.
anonymity and some protection from being traced.
Scalability
More tolerant of single-point failures than grids
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Utility Computing is
One of Several Commercial Drivers
(Based on a slide from HP)shared, traded resources
value
clusters
grid-enabled
systems
programmable data center
virtual data center
Open VMS clusters,TruCluster, MCServiceGuard
Tru64, HP-UX,Linux
switch
fabriccompute storage
UDC
computingutility or
GRID
today
Utility computing
On-demand
Service-orientation
Virtualization
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Utility Computing
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Grid Computing - Next Internet
NETWORK
IMAGINGINSTRUMENTS
COMPUTATIONALRESOURCES
LARGE DATABASES
DATA ACQUISITION PROCESSING,ANALYSIS
ADVANCEDVISUALIZATION
Grid Computing: Concepts, Applications, and Technologies Ian Foster, May 2002
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The Global Community
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Wireless and Mobile Applications
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So Far
Introduction
What is the Grid? What is Grid Computing?
Wireless Grids
Motives and Driving Forces
Infrastructure
Performance
Hybrid Grid Project Proposal
Grid Examples
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Research Challenges in Mobile Grid
Environments
InternetInternet
LAN
Grid
LAN Grid
Wire/Wireless
Gird
Arrivingusers/serversDeparting
users/servers
Static model
Stable servers
Stable users
Dynamic model
WLAN Grid
HeterogeneityHeterogeneityIntermittentIntermittent
AvailabilityAvailability
Small devicesSmall devices
Power deficiencyPower deficiency Limited NBWLimited NBW
MobilityMobilityNatureNature
SecuritySecurity
DynamicDynamic
ConnectivityConnectivity
http://www.wirelessgrids.net
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Driving forces
New User Interaction Modalities and Form
Factors Extend UI to small screens, small keyboards, and
other I/O modalities.
Speech
Issue of mobile device connectivity
Limited Computing Resources
Mitigate the constraints imposed by limitedresources of mobile devices.
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Driving Forces
Additional New Supporting Infrastructure
Elements Address new applications that involve dynamic
and unforeseen events.
Rapid provisioning of major amounts of computationaland communications bandwidths.
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A Scenario
Other scenarios: scientific application,commercial business
Forest fire
Firemen
Firemen
FiremenFiremenComputation center
History databases
Geographic
databases
Fire simulationWeather forecast
Wireless
links
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Marketting the wireless gridA self-sufficient economic model for mobile devices involved in grid computing.
T. Phan, L. Huang, C. Dulan, Challenge: Integrating Mobile Wireless Devices Into the Computational Grid,Proceedings of the 8th annual international conference on Mobile computing and networking. September 2002,pp 271-278.
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Grid Classification by Architecture
Classification by Architecture
Degree of heterogeneity of the actual devices Level of control exercised by those who own and
administer the devices.
Local Cluster or Homogeneous WirelessGrid
Wireless devices that share the same hardwarearchitecture and the same operating systems.
E.g.: Network of mobile handheld devices forcoordinating medical personnel in the hospital.
A. Agrawal, D. Norman, A. Gupta, Wireless grids: approaches, architectures, and technical challenges, MIT
Sloan Working Paper No. 4459-04; Eller College Working Paper No. 1016-05
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Grid Classification by Architecture
Wireless Intra-Grids
Encompasses wireless devices that belong to multipledivisions or communities within an actual organization(AO).
Divisions may be located in different geographies.
Divisions may be governed by a separate set of policies.
But there exists a level of trust and oversight so that groundtruth may be known with respect to identity andcharacteristics.
E.g.: wireless grid that simultaneously supports the mobile
sales force of a company and the networks of wirelesssensors used by the manufacturing division for trackinginventory
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Grid Classification by Architecture
Inter-Grid
Encompasses multiple AOs and transcends greateramounts of geographical, organizational, and other types of
differences, such as ones related to intellectual property
rights and national laws.
Resource management and policy integration (security,authentication and data management tasks) attain greater
complexity due to the scalability requirements.
A (potentially) universally accepted method for the
composition of declarative policies must be proposed andaccepted.
Commonly accepted semantics for the expression of policy.
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Grid Classification by Architecture
A. Agrawal, D. Norman, A. Gupta, Wireless grids: approaches, architectures, and technical challenges, MIT
Sloan Working Paper No. 4459-04; Eller College Working Paper No. 1016-05
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Grid Classification by Usage Pattern
Computational Grid
Virtual metacenter. Large amount of computing and data resources.
Data Grid
Provide shared and secure access to distributed data.
Large scale data processing and management that require
the participation of world wide researchers.
Utility Grid
Human interface of computational Grid and Data Grid.
Parasitic Computing, A-L Barabasi, V. W. Freeh, H. Jeong, J. B. Brockman, Nature, Vol. 412, 30 August 2001.
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Wireless Grid Contributions
Computational Grid
Ability to borrow computational resources fromothers.
Power limitations of mobile devices limits their
computational capabilities.
Cooperative or parasitic*.
E.g.: Wireless sensor network used to monitor
conditions for predicting natural calamities like
earthquakes or volcanoes.
Parasitic Computing, A-L Barabasi, V. W. Freeh, H. Jeong, J. B. Brockman, Nature, Vol. 412, 30 August 2001.
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Wireless Grid Contributions
Data Grid
Provide shared and secure access to distributeddata.
Integration and reconciliation of underlying data
semantics continues to challenge evolving technology.
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Wireless Grid Contributions Data Grid
ExamplePatient needs blood
Hospital issues query to
medical history databases
through its mobile network
Mobile ISP notifiespotential donors
Responses processed
and reconciled
Patient Gets blood
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Wireless Grid Contributions
Utility Grid
Also referred to as Access Grid Ubiquitous access to specialized pieces of
software and hardware
Users can request resources when needed (on-demand)
On-demand access to all kinds of resources
Only be charged for the amount being used. Can subsume both Computational and Data grids
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Wireless Grid Contributions Utility Grid
Example
Traffic conditions
and routing
Commercial products
and services
Instantaneous
decisions and
Transactions
Processing power
where its neededSensor networks
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Wireless Grid Resources
Provide a virtual pool of computational andcommunications resources.
Computing Power Overcome limited computation power on mobile devices by
distributing task across multiple devices.
Need for appropriate collaborative processes between thesegeographically distributed tasks.
Storage Capacity No more limited storage problem.
Distribute data across multiple devices. Avoid contention through the application of advanced
synchronization techniques.
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Wireless Grid Resources
Communications Bandwidth
Remote access, and high QoS.
Multiplicity of Applications
Ubiquitous access to a wide variety of
applications. Overcome the need to install these applications on
separate mobile devices.
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Grid Topology
A number of researchers have evaluated the
topology and configuration of mobile networks1
. standalone in nature.
Commercial wireless grids need to possess some
access to the Internet and wired Grid infrastructure;
therefore it is better to follow a hybrid model by
integrating Baseline devices into current wired grids.
It will consist of Mobile Ad-hoc Networks2 (MANET) type
systems with multiple-hop paths between mobile nodesand access points to the wired network.
1MANETconf: Configuration of Hosts in a Mobile Ad Hoc Network, S. Nesargi, R. Prakash, in Proc. of INFOCOM02, 1059-1068, 2002.Weak Duplicate Address Detection in Mobile Ad Hoc Networks, N. H. Vaidya,MIBIHOC2002, June 2002.
IP Address Assignment in a Mobile Ad Hoc Network, M. Mohsin, R. Prakash, IEEE Military Communications Conference (MILCOM 2002), Vol. 2, 856-861, October 2002.
2 http://www.ietf.org/html.charters/manet-charter.html
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Infrastructure
Grid systems are usuallyarranged in a hierarchal
manner, with a set ofnodes designated as thegateway.
The gateway managestasks such as:
Node management, Task allocation, and
Brokering.
All nodes on the grid willrun a client application
implementing a lightweight communicationsprotocol for informationexchange with the grid.
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Infrastructure - Brokering Service
Brokering Service The Brokering Service
facilitates all communication among thedevices participating in the grid activities1.
Two major information stores:
Active Agent Repository (AAR)
Task Allocation Table (TAT).
1A collaborative problem-solving framework for mobile devices, S.Kurkovsky, Bhagyavati, A. Ray, ACMSE '04, April 2-3, 2004.
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Infrastructure - Brokering Service
AAR contains information about all computingdevices that are available to the grid All mobile devices within a given wireless cell.
CPU rating, amount of available memory and the current levelof the battery charge.
TAT contains information describing how each
distributed task is allocated across the agents on thegrid. Information stored in TAT evolves as the distributed task
gets closer to completion.
When agents complete their partial tasks, they return theresults back to the Brokering Service, which stores them inTAT where they await to be requested back by the initiatorof the corresponding task.
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Infrastructure - Keep-Alive Server
All communication aspects of the grid
infrastructure are handled by the Keep-AliveServer.
sends and receives messages to and from all
computing devices available on the grid. All devices entering the wireless cell and willing to
participate in the distributed grid tasks advertise
themselves as available to the Keep-Alive Server.
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Performance Issues
Problems arise since meaning of performance isextended Computational performance: scheduling
Energy: power management and offloading
Unstable network: adaptation
Security
Addressing and naming
Discovery
Policies
A lot can be borrowed from other research areas, but
they should be put into a real Mobile Grid framework forinspection.
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Performance Issues
The mobility of the Baseline devices in the grid is a
critical factor affecting the performance of the entiregrid.
Directly affects the time it may take to perform a
computationally-intensive task.
Mobile devices overwhelming the underlying services suchas the Brokering service and Keep-Alive server.
Instability due to large number of mobiles leave the cell at
the same time.
Lack of sufficient resources.
Load balancing techniques to address this issue.
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Performance Issues
A related issue is that of agents systems leaving the grid whilepartial tasks are still in progress.
A solution is to re-allocate these partial tasks to other agentspresent on the grid.
Another approach is to allow agents to carry their partial taskswith them when they leave the grid and migrate to a new servicearea.
Handoff issues become paramount. What is to happen when the initiator of a task moves to a new area?
If the grid were to facilitate task completion even when the initiatorhas migrated to a different area, handoff issues once again become asignificantly complicating factor. Soft handoff has to be ensured for the agent migration so that the user is
unaware of the underlying issues involved with migration. Handoff issues need to be addressed by architecture.
Frequent disconnections lead to poor QoS.
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Performance Issues: Application Level
Scheduling Goal of scheduling: maximize application performance.
Application Level Scheduling (AppLeS)
An application-specific approach to build scheduler for parallel applicationson heterogeneous systems.
Comprehensive system and application information
Static information
User-specified application parameters
Application performance model Dynamic information: Network Weather Service
Performance prediction: Network Weather Service
Experience the system from the point view of application
Run-time scheduling: Information is applied to application model to estimate
application performance and choose an optimal resource allocation from aset of viable configurations.
F. Berman, R. Wolski, S. Figueira, J. Schopf, and G. Shao, "Application-Level Scheduling on
Distributed Heterogeneous Networks." In Proceedings of Supercomputing 96, Pittsburgh, PA, Nov.1996.
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Scheduling Algorithms: host-satellite
systems Host-satellite system
A powerful host and many less-powerful satellites
Offloading computation from satellite to host to
maximize overall performance Fit the scenario of mobile environment
Partitioning algorithm Requirements
Serial program
Pipeline processing Chain structure
Construct assignment graph for the partition problem. Weight for edges (Wh, Ws)
Find the optimal sum-bottleneck path in the
assignment graph Complexity: O(n2loge)
Shahid H. Bokhari, "Partitioning problems in parallel, pipelined and distributed computing." IEEE
Transactions on Computers, 37(1):48-57, 1988.
host satellites
s
1 2 3 4
1 2 3 4
1 2 3 4
t
1
2
3
1 2 3 4
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Saving energy.
Energy crisis of mobile devices Performance also concerns energy
Energy consumption estimation Simulation: SimplePower, Wattch
Empirical methods
Ways to save energy
Dynamic power management (DPM) policies: tradeoffbetween energy and performance Spin down disks
Turn off screen
Network interface hibernation
Processor voltage scaling Comprehensive stochastic model
Computation offloading
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Policy optimization of DPM Policy optimization
Most aggressive policy is not acceptable.
Find the balance of aggressiveness to optimize performance and energy consumption.
Stochastic model: Discrete-time Markov decision processes Model: service provider, service requestor, queue
Power manager makes random decision according to current state of SP, SR, Q, at each timeperiod.
Minimize performance penalty while keeping average energy consumption and request lossbelow some levels specified by users.
Advantages: generality, abstraction, non-determinism.
G. A. Paleologo, L. Benini, A. Bogliolo, G. De Micheli, "Policy Optimization for Dynamic Power
Management." Design Automation Conference, pp. 182-187, June 1998.
Power Manager
Service Provider Service Requestor
Queue
Observation
Command(on/off)
Request(0/1)
offonOff/0.8On/1.0
Off/0.2
On/0.0
Off/0.0
On/0.03
Off/1.0
On/0.97
Service Provider
100.95
0.05
0.12
0.88
Service Requestor
10-,0/1.0
On,1/0.8
Off,1/0.0
-,0/0.0
On,1/0.2
Off,1/1.0
on,0/0.8
On,1/0.0
Off,-/0.0
On,0/0.2
On,1/1.0
Off,-/1.0
Queue
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Computation offloading
Scheduling in terms of energy: Offloading can reduce computation, but communication also
consumes energy
Optimize energy consumption by offloading part of computation Model a program
Task definition: each call site (statically); each invocation(dynamically)
Cost graph
Relationship between tasks and data Node weight indicating power consumption of computation and
communication
Edge weight indicating mean number of times for tasks accessing data
Aggregate the consumption from the cost graph and optimize
Zhiyuan Li, Cheng Wang, Rong Xu, "Computation offloading to save energy on handheld devices: a
partition scheme." In Proceedings of the international conference on compilers, architecture, andsynthesis for embedded systems, Atlanta, Georgia, USA, 2001.
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Disconnected Operation
Another fact affects performance: unpredictablenetwork link quality Solution: adaptation
Disconnected operation in Coda file system Definition
a mode of operation that enables a client to continueaccessing critical data during temporary failures of a shared
data repository. Solution: proxy + cache
Venus: client-side proxy
Three working states Hoarding (Caching)
Emulation Reintegration
James J. Kistler, M. Satyanarayanan, "Disconnected Operation in the Coda File System." ACM
Transactions on Computer Systems, Feb. 1992, Vol. 10, No. 1, pp. 3-25.
Hoarding
Emulation Reintegration
Disconnection
Physical
reconnection
Logical
reconnection
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Application-aware adaptation
Application-aware adaptation model Operating System notifies application of relevant changes.
Accurate and timely information.
Application decides how to adapt to the changes Design of Odyssey: proxy again
Extension of NetBSD Typed data
Working model: Application requests data within a range of availability Odyssey returns data or notify change
Application re-request data of different quality usingdifferent range
Implemented as VFS in NetBSD system Requests are intercepted as system call
Advantages: agility, smooth running, support of concurrency
Brian D. Noble, M. Satyanarayanan, Dushyanth Narayanan, James Eric Tilton, Jason Flinn, Kevin R.
Walker, "Agile Application-Aware Adaptation for Mobility." In Proceedings of the 16th ACMSymposium on Operating System Principles, St. Malo, France, Oct 1997.
Application
warden
warden
warden
interceptor
Odyssey
viceroy
Kernel
syscall Odyssey
call
upcall
b l
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Mobile Security
Difficulties of security in wireless mobileenvironment Inherent vulnerability of wireless media
Performance impact!
Charon: indirect authentication using Kerberos Extend Kerberos by inserting a remote proxy (again!!)
between client and other servers
Secure channel is built by first granting the proxy service toclient
Proxy interacts with other servers on clients behalf
Client can be very small: only need DES encryption/decryption
No compromise of security: The communication between client and proxy is encrypted
Proxy believes the identity of user
Proxy does not possess clients session key and private key
Armando Fox, Steven D. Gribble, "Security on the move: indirect authentication using Kerberos." In
Proceedings of the second annual international conference on Mobile computing and networking(MobiCom'96), Rye, New York, United States, 1996.
Add bili d l i i d d i
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Address mobility and location independent naming
Wireless mobile networks
Nomadic network: Mobile IP Ad hoc network: ad hoc routing protocols
Nomadic network Ad hoc network
M bil IP
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Mobile IP
Problems Stable connection requires stable IP stable routing no mobility
Solution: associate two IPs with one host (one for identification, one for
routing)
Mobile IP
Charles E. Perkins, "Mobile IP", IEEE Communications Magazine, May 1997.
Home
Network
Home
NetworkForeign
Network
Foreign
Network
IP Host
Home
Agent
Foreign
Agent
Home IP Care-of IP
Home IP
Tunnel
Intercept
Ad h k
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Ad hoc network
No static or centralized infrastructure
Packet relay: routing
Efficient routing protocols are required to address Power limitation of the end devices
Consideration for stable wireless connectivity, routeoptimization and efficient use of the limited bandwidth.
Data will need to flow across the grid using a combinationprotocols
Mobile IP
Ad-Hoc routing protocols: Dynamic Source Routing Protocol (DSR) and
Ad hoc On-Demand Distance Vector Routing (AODV) Zone Routing Protocol (ZPR) Hybrid routing
Ad h i
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Ad hoc routing
Ad-hoc On-Demand Distance Vector Routing (AODV)
Pure on-demand route acquisition
Discover and maintain a route to another node onlywhen Need to communicate with the node
Current node acts as an intermediate forwarding node
Timeout to purge outdated path
Only reinitiate path discovery when moving node lyingalong active path
Monotonic increasing sequence number to supercedestale path
Pros: scalability, efficiency, responsiveness to change
C. E. Perkins, E. M. Royer, "Ad-hoc On-Demand Distance Vector Routing." In Proceedings of the
2nd IEEE Workshop on Mobile Computing Systems and Applications, New Orleans, LA, February1999, pp. 90-100.
Ad h ti
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Ad hoc routing
The Dynamic Source Routing protocol (DSR)
Simple and efficient routing protocol designedspecifically for use in multi-hop wireless ad hoc
networks of mobile nodes.
Completely self-organizing and self-configuringnetwork.
No need for any existing network infrastructure or
administration.
Dynamic route discovery
Dynamic Source Routing in Ad Hoc Wireless Networks, D. Johnson, and D. Maltz, Mobile
Computing, Vol353. Chp 5, pp. 153-181, 1996.
Ad h ti
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Ad hoc routing
Zone Routing Protocol (ZRP) combines: Proactive protocol: which pro-actively updatesnetwork state
and maintains route regardless of whether any data trafficexists or not
Reactive protocol: which only determines route to adestination if there is some data to be sent to
thedestination All nodes within hop distance at most dfrom a node X are
said to be in the routing zone of node X g All nodes at hopdistance exactly dare said to be peripheral nodes of node
Xs routing zone. Pro-actively maintain tables
Dynamically discover routes. Similar to DSR.
Peer to peer reso rce ro ting
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Peer-to-peer resource routing
Difference with Grid No distinguished server: anywhere (scalability)
Unstable nodes: join/leave (reliability)
Problems: how to find resource in peer-to-peer network? Keep each resource location at each node: not scalable
Flooding (Gnutella): not scalable
Centralized index server (Napster): single failure
P2P routing algorithms (distributed hash table): Content Addressable Network (CAN): distributed 2D hash table
Chord: ring-based structure
Pastry: Plaxton-tree based
Tapestry: Plaxton-tree based
Similarities and differences between ad hoc routing and P2P routing Sims: high mobility and low reliability of nodes, hop by hop connection, flat
network topology, etc.
Diffs:purpose of usage, node-node connection, abstraction level, routing table,etc.
Pastry 43C942 2 L2L3
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Pastry
Plaxton-tree-like structure Distributed tree structure where every node is the root of a tree
Simple mapping from object ID to root ID of the tree it belongs to
Nodes keep nearest neighbor pointers differing in 1 ID digit Hashed ID for both node and document
Routing table (O(logN)): digit similarity
Leaf set: numerically closest nodes
Routing (O(logN) hops) First check leaf set Then use routing table to forward message (1+ more digit)
Finally check ID with longest prefix and closest value
Pros Highly distributed (reliability)
Scalability Efficiency
A. Rowstron, P. Druschel, "Pastry: Scalable, distributed object location and routing for large-scale
peer-to-peer systems." IFIP/ACM International Conference on Distributed Systems Platforms(Middleware), Heidelberg, Germany, pages 329-350, November, 2001.
4227
6F43 1D76
44AF
42A2
L1 L1
L2
L2
L3
CE75 39AA
4A6D
4361
437A
43784378
4378
Discovery Semantics and Protocols
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Discovery Semantics and Protocols
Service description protocols are needed to describethe services provided by various components of the
wireless grid. Once the services are published, a discovery
protocol is needed to map the mobile resources tothe services. The notion of grid service can be
extended to the wireless grids. Some work has been performed towards providing
naming service for MANET systems.
The mobile nature of the wireless grid components
makes it challenging to provide for discoverymechanisms across virtual organizations.
Policy Management
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Policy Management
Since the end-devices or nodes can be power
constrained, one cannot assume that the devices
are capable of running complex protocols such as
Lightweight Directory Access Protocol (LDAP) or
Common Open Policy Service (COPS).
Need to address policies that govern the usage,privileges, access to resources, sharing level
agreements, quality of service, and the
composability and the automated resolution ofcontradictory policies among organizations.
W. Adjie-Winoto, E.Schwartz, H. Balakrishnan, J. Lilley, The Design and Implementation
of an Intentional Naming System, Proc. 17th ACM SOSP, Kiawah Island, SC, Dec. 1999.
So Far
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So Far
Introduction
What is the Grid? What is Grid Computing?
Wireless Grids
Motives and Driving Forces Infrastructure
Performance
Hybrid Grid Project Proposal Grid Examples
A proxy based hybrid Grid
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A proxy based hybrid Grid
Addresses:
Scalability. Integratability with current technology.
Stability
Decrease mobiles computational overhead. Hide heterogeneity.
Ease of scheduling.
Service discovery
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Hybrid Grid
Organized mixof wireless and
wired gridnodes.
Heirachaldesign.
Proxy agentsact as mobiledevicesgateway to the
Grid.
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Hybrid Grid
Proxy agent
Can be any device on the grid. Including a mobiledevice with appropriate middleware.
Ideally co-located with the wireless access point.
Amount of resources depend on the demand. How many mobile devices does the proxy agent serve?
Mobile devices can be invisible to the rest of thegrid.
Proxy agent will represent them to the rest of thegrid. Less responsibilities.
T. Phan, L. Huang, C. Dulan, Challenge: Integrating Mobile Wireless Devices Into the Computational Grid,
Proceedings of the 8th annual international conference on Mobile computing and networking. September 2002,pp 271-278.
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Hybrid Grid
Within the Grid the proxy agent runs
appropriate middleware, such as Globus, topublish itself as a node.
Contribute a certain amount of computational,
networking,and storage resources. Aggregate total of the resources of the proxys active
agents.
Proxy agent handles resource requests.
E.g.: CPU Time
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Hybrid Grid
The proxy agent decomposes the request;
Problem and data partitioning is known to be a difficult task within
the parallel computing community* Assume that a subsystem will provide the tools needed to
successfully distribute the problem
E.g.: a descriptive hint to distribute a 2-D array using blockpartitioning.
Wait for results and sends them back to the requester.
Aggregate the data before responding.
Reduce per-message overhead.
Requests for data distribution or storage are handled the same
way.
V. Kumar, A. Grama, A. Gupta, and G. Karypis. Introduction to Parallel Computing, The BenjaminCummings Publishing Company, 1994.
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Hybrid Grid
Advantages:
Clustering technique suited for managing looselyassembled group of devices.
Similar technique used for routing in:
Bluetooth, Landmark routing, Mobile IP,ALICE, CORBA-
enabled applications.
KaZaA: peer nodes are clustered around so-called
supernodes
FastTrackJ. Haartsen. BLUETOOTH - the Universal Radio Interface for Ad-Hoc Wireless Connectivity,Ericsson Review, no. 3, 1998.G. Pei, M. Gerla, and X. Hong. LANMAR: Landmark Routing for Large Scale Wireless Ad Hoc Networks with Group Mobility, In Proceedings ofIEEE/ACM MobiHOC, August 2000.K. Truelove and A. Chasin. Morpheus Out of the Underworld, www.openp2p.com/pub/a/p2p/2001/07/02/morpheus.html
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yb
Advantages: Proxy agent reduces communication between requestor
and each cluster node. Takes burden off each mobile device.
Scalable, because proxy agents dont have to be verypowerful and more of them can be installed as needed.
Cellular tower upgrade? Mobile devices can autonomously decide and publish their
own resources through the proxy agent.
Because user may want to choose times when they want to
give processing time to the Grid. Proxy can adjust total available resources based on its active
agent reliability.
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y
Advantages: Proxy agent can cache individual requests to particular
active agents. Partially hiding connectivity deficiencies.
Results can be cached until the aggregate total is collectedif need be.
Hide heterogeneity of the mobile devices. The proxy can make scheduling decision by accessing the
power consumption metrics of the Mobile device.
Simple service discovery
Only need to locate proxy. DHCP, Jini, the Service Location Protocol, and expanding ring IP
multicast.
Example Wireless Grids
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p
DARC* Audio mixing application
Multilevel Triage System sensor networkpatient monitoring.
Supply Chain Asset monitoring.
Access GRID group to group interactionacross ZGRID
DARC*
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The Syracuse university research team is building asample application to demonstrate the potential.
Application allows devices with no prior knowledgeof each other collectively record and mix an audiosignal such as a concert, speech, lecture, oremergency event.
The project demonstrates the potential of wirelessgrids and distributed ad hoc resource sharing toharness the combined ability of mobile devices in
social contexts outside the expected environmentsfor
DARC* wireless grid interface
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g
DARC* Process Flow
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Application consists of a mixerand two ormore recorders.
1. A user wishing to initiate a recording sessionelects to act as either or both a mixer and arecorder and waits for the involvement of a
second recording service.2. Recording begins once two services have
registered with the mixer.
3. The recorders stream the recordings to the mixer.
4. The recorders then initiate a listening service toreceive the mix back from the mixer.
Multilevel Triage System Architecture
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g y
At each site, eachemergency medical
technician has vitalsign data (such asEKG, blood oxygenlevel, and pulse) for
each patient.
The system offersedge-based control
with centralmanagement ofglobal resources.
Supply Chain Asset Monitoring
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After checking in (1), deliverytrucks are either stacked up
(2) to await being unloaded orare sent to an unloading dock(3).
As the truck is unloaded, eachitem can be sensed as it moves
into the warehouse on thecentral conveyer belt.
Items can be located within thewarehouse (4), and as they are
shipped out (5) to stores orcustomers.
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Summary
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Next generation of computing.
Incorporating mobility into Grid architecture isnecessary and beneficial to both user and
computing community.
Problems arise since meaning of performance isextended.
Encompasses many research areas.