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![Page 1: [IEEE 2009 First International Conference on Advanced Computing (ICAC) - Chennai, India (2009.12.13-2009.12.15)] 2009 First International Conference on Advanced Computing - Security](https://reader031.fdocuments.us/reader031/viewer/2022030302/5750a4fc1a28abcf0cae9119/html5/thumbnails/1.jpg)
Security in Mobile Grid Service Varalakshmi P, Thamarai Selvi S, GaneshKumar R, Sundar Raman S
Department of Information Technology
Madras Institute of Technology Chrompet
Anna University, Chennai, Tamilnadu, India
Abstract— Mobile Grid is one of the recent emerging
technologies. It has a lot of challenges due to the scarcity
of resources such as processing power, persistent storage,
runtime heap, battery lifetime, memory, bandwidth, and
connectivity and network faults. Dynamic environment affects
both mobile and non-mobile grids. This creates a need for the
virtual administrator. Virtual Organization (VO) is
responsible for resource coordination and to support
Authentication, Authorization and Accounting (AAA).
Dynamic Mobile Virtual Organization (DMVO) has
the property of VO in addition to features such as
workflow initiation and handling of mobile nodes. We
analyze the various types of mobility such as user
mobility, session mobility and resource mobility for
implementing a mobile grid. We have concentrated on the OSI
layered approach for mobile grids and how it helps in the
process execution. We analyzed Service Level Agreement
(SLA) and how it helps for negotiation and
monitoring. We have analyzed the performance
measures for Job Execution Cost, Bandwidth Utilization
Factor, Rejection Ratio for different number of jobs and
various clusters such that each cluster contains different
number of nodes with different configuration. Our main
aim is to decrease the Job Execution Cost and to increase
bandwidth utilization factor compared to the existing scenario.
Keywords: Mobile Grid, Service Level Agreement, Dynamic
Mobile Virtual Organization, Job Execution Cost.
I. INTRODUCTION
Mobile Grid is an emerging grid like Ad hoc and wireless
grids. The Mobile Grid network consists of mobile nodes
that are connected through wireless links, as opposing to the
conventional networks and follow a random topology. This
topology may change dynamically and it is unpredictable.
Mobile Grids are the one that have the capability of
executing any node’s process and send back the result to the
original node that needed the execution of the process. The
characteristics of a mobile network like dynamic topology,
restricted bandwidth, different link capacity and high error
rates makes it hard to bring the security measures in it. But
for the resource sharing and resource coordination we are in
need of a virtual administrator. We simulated three types of
mobility for Grid nodes and how the Mobile Grid works in
these scenarios. For security measure we are in need of a
different SLA that will work on all situations. We
implemented Mobile Grid protocol (MG protocol) that will
support such security measure.
This paper is organized as follows. Session 2 presents the related work on emerging grids particularly Mobile Grid.
Section 3 discusses about the requirement of virtual
administrator in Mobile Grid. Section 4 discusses about the
three mobility types in Mobile Grid. Section 5 discusses
about the Description of the proposed MG protocol. Section
6 discusses the performance evaluation for the MG protocol.
Section 7 gives the conclusion and future work.
II. RELATED WORK
Emerging grids are classified into various types such as
manageable, interactive and user-centric Grids. Knowledge
Grids come under manageable grids. Former is for managing
the human nervous system and support self managing and
the latter represents the usage of different knowledge
management mechanism to support self managing. Personal
Grids come under user centric grids which are similar to
PCs, where each grid is owned by an individual. Interactive
Grids are explicit interactive grids and context aware grids.
In which the former support explicit real time interaction
with users and the later interacts with the surroundings to
build context and adapt their behavior. Mobile Grid, Ad hoc
Grid, Wireless Grid are accessible grids. Ad hoc Grids have
no predefined entry points and wireless grids support
wireless connections between grid nodes and interface.
Konstantinos Katsaros and George C. Polyzos discussed
about why to bring Mobile Grid and they had made a survey
in both technical and business oriented approaches to bring
the Mobile Grids. Stefan Wesner discusses about the
architecture of the Mobile Grid and describes a SIMPLE
protocol for message passing between the agents. F.
D’Andria tells about the theoretical views of the SLA
management subsystem about the SLA management and
SLA negotiation. Waldburger M and Stiller B investigated
in which sense a mobile grid needs functional extensions
and what type of consequences the integration of mobile or
nomadic grid resource will cause. Antonios Litke et al
discussed about the basic infrastructure of mobile grid
services. Sze-Wing Wong and Kam-Wing Ng constructed a
mobile grid agent by combining existing mobile agent
system, Java Agent Development Framework (JADE).
Shang-Fen Guo et al proposed a new service called grid
mobile service (GMS), an extension of grid service and they
discussed about the agent’s lifetime and state evolvement in
GMS. T. Kirkham et al proposed a model for an application
where network based security can be scaled into Grid
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middleware security in a seamless application execution
scenario. Michael Messig and Andrzej Goscinski mainly
concentrated on the need of transparent autonomic
management in service oriented grids and they have
demonstrated the design and implementation of a System
Management Broker.
III. VIRTUAL ADMINISTRATOR FOR MOBILE GRID
A. Mobile Grids
Mobile grids make grid services accessible through
mobile devices such as PDAs and smart phones as in Fig 1.
We usually consider these devices to be at the best
marginally relevant to grid computing because they’re
typically resource limited in terms of processing power,
persistent storage, runtime heap, battery lifetime, screen size,
connectivity and bandwidth.
B. Mobile Grid Architecture
The mobile nodes can be integrated to form an
infrastructure known as a Mobile Grid. Basically a grid is a
system that coordinates resources without the knowledge of
a centralized server. There are three categories of nodes present in a grid Consumer Node (CN), Service Provider
Node (SPN), and Grid Head Node (GHN) where CN
requests a service; SPN provides the service and GHN which
is used to manage all the other nodes. A lot of models are
available to present the Movement of mobile nodes.
Figure 1 Mobile devices and services
C. Dynamics Virtual Organizations
Dynamic Virtual Organizations (DVO) can be applied
for both non-Mobile Grids and Mobile Grids. Dynamics in
non-Mobile Grid systems corresponds to dynamic
organizational constitution and to dynamic process execution
based on only the current needs. But we have to consider
high level of dynamics for Mobile Grids since large number
of handoffs and handovers get executed within a short
interval of time. Mobile Grid increases complexity since the
contents of organizational constitution change rapidly and
we have to maintain the sessions and services in a accurate
manner. Dynamics are used as the key driver for customized
Mobile Grid.
D. Dynamic Mobile Virtual Organization
The target of basic Mobile Grids are service provisioning
for nomadic users. Provisioning often appears in the context
of virtualization, orchestration, utility computing and open
configuration concepts. VO arises due to the strong focus on
inter-domain service provision and service virtualization.
They are also referred to as virtual enterprises or virtual
communities. The concept of VO has been evaluated and its
notion has been evolving over time. VO is considered for
information and communications technology that supports
accountable and chargeable resource coordination across
administrative domains and also to support Authentication,
Authorization and Accounting (AAA). The concept of VO is
changed for Mobile Grids to support Dynamic environment.
Here it refers to the nodes that are not fixed and move to
some other location. It has to be considered well for the
joining and leaving of nodes in a short period of time. The
concept of VO must be employed for resource coordination
and AAA. And it must be extended to support mobility by
adding additional features so that the nodes change their
locations at any point of time and that the workflow is
initiated according to the environment. Generally Grid
follows Distributed mechanisms but Mobile Grid has a
virtual centralized server.
The challenges to be handled while designing a central
administrator are their Membership Management and
Service Provider Selection. The administrator has to handle
the nodes effectively that does not give prior information
about their status. These nodes can go off line at any point of
time. In that stage the node which requests a process from
that off line node gets hanged and does not continue with its
execution. This leads to starvation for some point of time
IV. MOBILITY TYPES AND MOBILE GRID
In a Mobile Grid, all resources need not be mobile.
There are three types of mobility such as user mobility,
session mobility and device mobility. In the device mobility,
the terminals have the capability to move from one IP
(Internet Protocol) subnet to another without any
interruption (session or service interruption). In the user
mobility, as in Fig 2, the mobile devices form a group of
devices with respect to some logic addressing. The group is
addressed by one logic address (1-to-many addressing
scheme whereas one address maps too many logical
addresses). This scheme can also be combined with many-
to-1 addressing where various addresses map to one logic
address. But a given user can access a service or session at
different terminals. In Session mobility, it enables users to
keep sessions when moving from one device to another as in
Fig 3.
The main difference between the session mobility and
user mobility is that session can be only accessible at a
single point of time. By then, sessions are transferred
completely or in parts to any another terminal. These
mobility types are combinable, such that the users can
change the access networks and the service providers.
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Figure 2User Mobility in a Mobile Grid
Figure 3 Session Mobility in a Mobile Grid
A. Mobile Grid Layer
With the general OSI layer, Grid layer is added above
the application layer, as shown in Fig 4. On considering the
Mobile Grids, we should consider each layer to satisfy the
mobile characteristics. The physical layer uses wireless
propagation models such as sky level propagation and line
of sight propagation. In the data link layer, IEEE 802.11
standards are to be followed.
Figure 4 Grid Layer in OSI model
In the network layer, we have to consider routing
protocols such as AODV or DSR. In the transport layer, the
data processing between the two processes and monitoring
the sequential order of the process execution has been done.
The session layer is used to maintain synchronization
between the nodes and it is used to create session mobility
explained above. The presentation layer is the same as that
of the wired layer and the next one is application layer in
which an application is taken into account such as Android
or J2ME to create the user interface for the mobile nodes.
The next one is the grid layer for the execution of the
processes and maintaining the resource coordination and to
handle the vulnerable and off line nodes.
V. MG PROTOCOL
A. Service Level Agreements:
Since the link between the services is present in the Grid
Middleware and the underlying network has to be efficient,
the Mobile Grid computing environment with respect to
business applications becomes very critical in order to
support efficient implementation of monitoring, negotiation
and service management. We have developed a SLA
management subsystem to attain monitoring, negotiation
and service management. A notification mechanism is
added between the grid layer and network layer for effective
communication.
These SLA mechanisms should consider QoS parameters
for grid resources such as CPU use, Memory disk and the
network capabilities such as bandwidth. So, the
application’s QoS requests are mapped on these
infrastructure QoS parameters.
B. MG protocol:
MG protocol is designed to perform SLA negotiation,
monitoring and service management. The MG message
format contains Name, Context, Service Description terms
and Guarantee terms. Name refers to the current node, its
speed of execution and its memory limit. Context specifies
the information about the neighboring nodes and their
status. Service Description says their services, their lifetime
and their capabilities. Guarantee tells their rule for
executing the service, giving the guarantee that it will
execute within the time limit without considering factors
such as node mobility and resource scarcity. We cannot
guarantee that a service cannot be executed that is out of its
capability.
In this protocol, SLA negotiation works as follows. If
two nodes desire to transact in Mobile Grid environment,
the negotiation will share their policies of execution and the
best policy is chosen and it executes the process and the
remaining one is discarded. We can also follow the same
process for very large number of nodes that want to perform
any transaction in a Mobile Grid environment. If the node is
malicious and is problematic in negotiation, an alternate
policy is used immediately. (We have to create the policy
and an alternate policy at the time of SLA negotiation).
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VI. IMPLEMENTATION
Simulation studies are carried out in GloMoSim 2.03
under Linux environment. GloMoSim stands for Global
Mobile Simulator. It is used to build a scalable simulation
environment for mobile and wireless network systems. It is
being designed using the parallel discrete-event simulation
capability provided by Parsec, a C based environment. This
tool is taken since it supports different types of protocol in
each layer and we can add any protocol for our
compatibility.
Most network systems are currently built using a layered
approach that is similar to the OSI seven layers network
architecture. This allows the rapid integration of models
developed at different layers by different people. The
proposed protocol stack will include models for the channel,
radio, MAC, network, transport and higher layers.
We add modules for Mobile Grid by means of adding
another layer that is grid layer and establishing its
functionalities. To establish grid layers we are in need of
parameters such as processing speed, memory, network
bandwidth, network link and so on. We have created three
types of mobility that are already mentioned above. And it
gives better performance for large number of nodes and gets
executed faster due to Parsec which is used for parallel
simulation. We add some modules in driver.pc originally
present in GloMoSim and make it as driver_mobilegrid.pc.
And compile the pc file by means of pcc.
retval = GLOMO_ReadInt(-1,&nodeinput, "PACKET-
SIZE" , &packet_size);
assert(retval == TRUE);
retval = GLOMO_ReadInt(-1,&nodeinput, "PROCESS-
SIZE" , &process_size);
assert(retval == TRUE);
retval = GLOMO_ReadInt(-1,&nodeinput, "PROCESS-
DEADLINE" , &deadline_process);
assert(retval == TRUE);
We made certain fields such as Packet-size, process-size
and process deadline are mandatory. This is used to
determine whether the process can be executed by the
mobile nodes that participate in the Mobile Grid
environment.
If (process_size > no_of_nodes * CPU_memory) the loop is
exited. This constraint should be checked to find the
feasibility of the execution.
Then split the process n times, where n refers to the
maximum number of nodes. If P is the process that is going
to be executed in the Mobile Grid, P = <P1, P2 …Pn>.
Allocate each process with every mobile node <M1, M2…
Mn>. Results are passed to the original nodes and the
messages are sequentially ordered. After this, combine the
execution of all the processes.
To establish security, we go in for SLA agreement and a
new protocol is proposed. It’s necessary to add the
functionality of the protocol, into the driver.pc file. Add the
parameter agreement for that protocol by
retval = GLOMO_ReadInt(-1,&nodeinput,
"AGREEMENT" , &agreement);
If the agreement is not true, then the node will not form
as member in any Mobile Grid environment. The
parameters used for simulation is shown below in table 1.
Table1 Parameters for Mobile Grid Simulation
TERRAIN-DIMENSIONS (1200, 1200)
NODE-PLACEMENT RANDOM
MOBILITY RANDOM-WAYPOINT
MOBILITY-POSITION-
GRANULARITY 0.3333
PROPAGATION-LIMIT -111.0
MAC-PROTOCOL 802.11
NETWORK-PROTOCOL IP
NETWORK-OUTPUT-
QUEUE-SIZE-PER-
PRIORITY
100
ROUTING-PROTOCOL AODV
SEED 27
VII. SIMULATION AND RESULTS
A Job Execution Cost
In a grid, resource prices can vary depending on the
usage (working/non-working time) or the resource load
(peak/off-peak). Each node should have some threshold
cost. This decreases for increasing number of nodes and
increases for increasing number of jobs.
Table 2 Analyzing the Job Execution Cost
Number of jobs Job Execution
Cost
19
34
65
84
97
Existing model
385
480
712
930
1220
Proposed model
357
429
630
810
1005
Table 2 shows the job execution cost for increasing
number of jobs and analyzed in various types of clusters
with each one have different number of nodes and does not
have same configuration. Fig 5 shown below represents the
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Job Execution Cost
1400
1200
1000
800
600
400
200
0
19 34 65 84 97
No of Jobs
Previous Model Our Model
Job Rejection Ratio
0.5
0.4
0.3
0.2
0.1
0
14 22 37 58 67
No oj jobs
Our Model Previous Model
diagrammatic representation of the job execution cost
analysis.
Table 3 Analysis of Bandwidth Utilization Factor
Number of jobs Bandwidth
Utilization
Factor
34
43
62
87
96
Proposed
model
0.26
0.3412
0.492
0.690
0.761 Existing
model
0.20
0.2559
0.369
0.517
0.571
Figure 5 Analysis of Job Execution Cost
B. Bandwidth Utilization Factor
The ability to reserve network bandwidth is a critical
factor for the success of high-performance mobile grid
applications. Reservation of light paths in dynamically
switched optical networks facilitates guaranteed bandwidth.
However, reservation of bandwidth can often lead to
bandwidth fragmentation which significantly reduces
system utilization and increases the blocking probability of
the network.
C. Rejection Ratio
Rejection ratio depends on the following factors: number
of available resources in the grid and total number of jobs.
The jobs get rejected unexpectedly due to the mobility of
nodes. It does not follow any probability distribution but
follows random process.
of SPN
Bandwidth = Total number of jobs / Total number
Bandwidth factor = Bandwidth * Constant_factor.
Figure 7 Analysis of Job Rejection Ratio
We can increase / decrease the number of jobs and number
Bandwidth utilization factor increases when the number
of jobs gets increased and decreases when number of nodes
get increased.
Bandwidth Utilization Factor
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
34 43 62 87 96
Number of Jobs
Our Model Previous Model Figure 6 Analysis of Bandwidth Utilization Factor
Figure 6 shown above and Table 3 shown below
represent the analysis of Bandwidth Utilization Factor in
diagrammatic representation and Data set formats.
of SPNs. Figure 7 shown above and Table 4 shown above
represent the analysis of Job Rejection Ratio in
diagrammatic representation and Data set formats
Table 4 Analysis of Job Rejection Ratio
Number of jobs Job Rejection
Ratio
14
22
37
58
67 Proposed
model
0.04
0.08
0.28
0.2
0.26 Existing model 0.06 0.12 0.24 0.26 0.34
The performance measure for Job Execution Cost,
Bandwidth Utilization Factor, and Rejection Ratio are found
by changing the number of nodes in each cluster, number of
jobs and also changing the number of clusters.
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VIII. CONCLUSION AND FUTURE WORK
In this paper, we proposed a Mobile Grid protocol for
Mobile Grid’s Service Level Agreement. And then we have
modified the code of original GloMoSim that is actually
designed for wireless environment and make that for Mobile
Grid environment. This MG protocol will provides the
Mobile environment. If there are anomalies in the cluster
then it cannot form the Mobile Grid group. We have
decreased the Job Execution Cost and the rejection ratio,
and thereby effectively improving the bandwidth utilization
compared with the existing conventional model. SLA
negotiation and validation is done which will increase the
job execution speed. And we also simulated with various
type of mobility which can be made possible for any type of
job that is being executed. In future work we have to add
functionalities or should use some other simulator to make it
feasible for heterogeneous environment. We have to make
continuous assessment to decrease the rejection ratio and to
improve the bandwidth utilization factor.
IX. REFERENCES
[1] Konstantinos Katsaros and George C. Polyzos, “Towards the
Realization of a Mobile Grid”, International Conference On
Emerging Networking Experiments And Technologies,
Proceedings of the 2007 ACM Context conference, New York, Article No. 31,2007,ISBN:978-1-59593-770-4
[2] Michael Messig, Andrzej Goscinski, “Autonomic system
management in Mobile Grid environments”, ACSW '07: Proceedings of the fifth Australasian symposium on ACSW frontiers - Volume 68, Jan. 2007
[3] T. Kirkham, D. Lutz, J. Movilla, P. Mandic, J. Gallop, C.
Morariu, “Identity Management in a Mobile Grid Environment”, Proceedings of the UK e-Science All Hands Meeting 2007, ISBN 978-0-9553988-3-4, pages 636-642,
Sep.2007
[4] Sze-Wing Wong and Kam-Wing Ng, “Security support for
Mobile Grid Services Framework”, Proceedings of International Conference on Next Generation Web Services Practises, IEEE, 2006.
[5] Francesco D’Andria, Josep Martrat ,Giuseppe Laria, Pierluigi
Ritrovato, Stefan Wesner,”An Enhanced Strategy for SLA Management in the Business Context of New
Mobile Dynamic VO”, Exploiting the Knowledge
Economy: Issues, Applications, Case Studies Paul
Cunningham and Miriam Cunningham (Eds) IOS Press, 2006 Amsterdam ISBN: 1-58603-682-3.
[6] S. Wesner, “Towards an Architecture for the Mobile Grid”, it –
Information Technology, vol. 47, and issue 6/2005: The Grid
(by Oldenbourg Wissenschaftsverlag), ISSN 1611-2776, Dec- 2005
[7] Antonios Litke, Dimitrios Skoutas, Theodora Varvarigou,
“Mobile Grid Computing: Changes and Challenges of Resource Management in a Μobile Grid Environment”, Department of Electrical and Computer Engineering, National
Technical University of Athens, 9 Heroon Polytechniou Str., 15773 Athens, Greece.
[8] Shang-Fen Guo, Wei Zhang, Dan Ma and Wen-Li Zhang,
“Grid Mobile Service: Using Mobile Software Agents in Grid Mobile Service”, In proceedings of the Third International
Conference on Machine Learning and Cybernetics, Shanghai, 2004.
[9] Waldburger M, Stiller B, “Toward the Mobile Grid: Service
Provisioning in a Mobile Dynamic Virtual Organization”,
Computer Systems and Applications, IEEE International
Conference, Mar. 2006.
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