- Open Access
- Total Downloads : 146
- Authors : Nripesh Kumar , Purushottam Das , Shambhu Prasad Sah
- Paper ID : IJERTV3IS060229
- Volume & Issue : Volume 03, Issue 06 (June 2014)
- Published (First Online): 18-06-2014
- ISSN (Online) : 2278-0181
- Publisher Name : IJERT
- License: This work is licensed under a Creative Commons Attribution 4.0 International License
A Comparison of Migration Scheme of Mobile Agent in Aglet
Nripesh Kumar Purushottam Das Shambhu Prasad Sah
Deptt. of Computer Sc. & App. Deptt. of Computer Sc. & App. Deptt. of Computer Sc. & App GEHU, Bhimtal GEHU, Bhimtal GEHU, Bhimtal
Abstract-Mobile agents (MA) are autonomous and proactive software entities which act on behalf on an owner and have the ability to migrate through a heterogeneous network of computer. In mobile agent migration, migration strategy is responsible for movement of agent from one host to another, an efficient migration strategy provide the low computation power, low bandwidth utilization. Currently there are several agent platforms which provide different approach of migration. In this paper we compare push and pull oriented approach of migration and analysis the performance with cache mechanism on aglet mobile agent platform.
Keywords: Mobile Agent, Agency, Push, cache, migration
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INTRODUCTION
Mobile Agents is programs which represents a user in network, and have a ability to migrate from one host to another host [1]. A mobile agent has authority to make migration related decision. After migration to the desired host the mobile agent can resume its previous state. Therefore, there is no need to maintain a continuous connection between client and server. This will save the unnecessary load. When mobile agent migrates from one host to another, It is the responsibility of the agency to migrate the mobile agent from one host to another host. For migration, A agency can use several approach of migration. A best migration strategy can be select based on the several parameters like QoS, Pos, and SOS etc. QoS parameter means quality of services which is provided by a migration strategy during migration of a mobile agent. It is varied from 0 to 1. The QoS 1 indicate that the quality of service provided by a migration strategy is good and QoS 0 indicate that no service is provided.Pos parameter means price of service or cost of migration of mobile agent from one host to another.
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MIGRATION APPROACH
Migration strategy of mobile agent can be classified in to two category push and pull[4]. These migration strategies have a great impact on the performance of MA. In this paper we compare push approach of MA migration.
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Push All-to-Next
It transfers entire code to the next host, while sending the state of the mobile agent. This approach is virtually
dependent on the size of the code and does not impose a continuous load.
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Push-All-to-All
It transfers entire code of agent to all the host of a network. In this scheme mobile agent should know the entire destination before transmitting the code. When the MA arrives on the destination platform, MAs execution can start immediately without any further code transmission.
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PERFORMANCE ANALYSIS OF MIGRATION SCHEME
Aglet is a open source agent development platform, which is developed by IBM Japan. It is widely used for developing mobile agent, It provide complete support for java language. The basic architecture of aglet consists of two layer and sub- component Aglet Runtime Layer provides following functionality.
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Serialization and de- serialization of Aglets
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Class loading and transfer
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Reference management and garbage collection.
Fig. 1 [1]
A. Cache Manager
In aglet cache-manager is responsible to maintain unnecessary transfer of code during the migration. When mobile-agent maintain a connection then the local agency check which program code are cached , Cache mechanisms avoid an unnecessary transfer of code from a remote area by using data cached in the local area. At the first connection in mobile agent migration, the local area has to check which program codes are cached or not in the remote area, because Caching all MAs in the platform results in waste of storage
space. Therefore, the platform is required to choose MAs whose code should be cached, while migrating to another platform according to the policies provided in the MAS . Agent can be cached based on the mean number of visits of an MA to a platform during a given interval. Therefore, it is necessary to compute the mean number of visits of the MA to the platform from the time of MAs creation to the time of last visit of the destination. If the MA frequently revisits the platform, it is necessary for the platform to cache the MA code, in order to improve system performance. In addition, the execution time of the MA can be reduced by partially eliminating transmissions of the MA code.
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EXPERIMENTAL SETUP
The experiment are made with aglets2.5-alpha on three different machine, The first was equipped with 1.90GHz , 2GB memory with Ubuntu operating system ,the second was equipped with 2.53 GHz I3 CPU with 4GB memory , Ubuntu and JSDK1.7,and the third was equipped with a 2.40 GHz I5 CPU with 4 GB memory ,Ubuntu and JSDK1.7. This experiment was carried out to measure the MA migration cost of the two existing approach push all to next and push all to all with code caching mechanism. In our experiment MA has circulated the 3 nodes.
A. Performance Comparision
Table1.Push all-to-next without cache vs. using caching mechanism
Size of MA Code
(byte)
Migration Cost without
cache(ms)
Migration cost with
cache(ms)
Performance ratio
(%)
7.5K
65
55
118
64K
140
50
280
160K
275
47
585
push-all-to-next
push-all-to-next
56
54
52
50
48
46
44
42
migration cost with cache
1
2
size of code
3
migration cost
Fig. 2 (b)
Table 2. Push all-to-all without cache vs. using caching
Size of
MA Code (byte)
Migration
Cost without cache(ms)
Migration
cost with cache(ms)
Performance
ratio (%)
7.5K
170
55
309
64K
430
70
614
160K
840
104
807
mechanism
push-all-to-all
900
800
migration cost
700
migration cost without cache
600
500
400
300
200
100
0
300
250
200
150
100
50
0
1 2 3
migration cost
size of code
migration cost without cache
.
Fig. 3 (a)
push-all-to-all
1
2
size of code
3
Fig. 2 (a)
120
migration cost
100
80
60
40
20
0
migration cost with cache
1 2 3
size of code
Fig. 3 (b)
The migration cost of mobile agent is calculated by adding the freezing time of all the nodes or sites. From above table when the size of MA code is varied from 7.5K to 160K, the freezing time of caching-added scheme is lower than the freezing time of without caching scheme. As the size of MA code increases, the performance of the scheme is improved from 118% to 807%.
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CONCLUSION
This paper compares he two migration scheme push-all-to- next and push-all-to-all with the cache mechanism provided by the aglet platform. From the comparison it is clear that the cache manager available in aglet runtime layer provide the best performance in compare to general scheme.
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