Introducing The Different Challenges Regarding Trust Models in Grid Computing

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International Journal of Emerging Technology and Advanced Engineering

Website: www.ijetae.com (ISSN 2250-2459,ISO 9001:2008 Certified Journal, Volume 3, Issue 4, April 2013)

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Introducing The Different Challenges Regarding Trust Models

in Grid Computing

Sourav Gayen

1

, Avijit Bhowmick

2

, Biswajit Upadhyay

3

1

M-Tech(CST),Dept of C.S.E/IT, Dr. B.C Roy Engineering College, Durgapur, India, e-mail:[email protected].

2_{Asst. Professor, Dept of C.S.E/IT, Dr. B.C Roy Engineering College, Durgapur, India, e-mail:[email protected].} 3_{Asst. Prof., Dept of C.S.E/IT, Aryabhatta Institute of Engineering& Management,Durgapur, e-mail:[email protected]}

Abstract—Grid computing, being a gifted way for distributed

supercomputing. There are lots of challenges for grid computing, both from technical point of view and from nontechnical point of view and there are quite a few barriers from grid computing being widely accepted by common end users. Grid computing is taken to the next level which aids in the discovery and use of remote resources for computing and storage. The Grids create an illusion of a simple, large and robust self configuring virtual computer consisting of well connected heterogeneous systems sharing various resources. The users don’t need any direct control over the diverse resources of the Grid. A major difficulty for Grid services is how to gain confidence that a distant system is performing in accordance with their norms. Proper resource distribution and deployment cannot be achieved unless trust is established in the

Grid. In this paper we have discussed different challenges and

barriers for the improvement and usage of grid computing are listed.

Abstract— Grid Computing ,Trust ,Challenges .

I. INTRODUCTION

Grid computing is a coordinated resource sharing and problem solving in a dynamic environment. Grid Computing concept was first visualized by Leonard Kleinrock in 1969 when it was written “We will probably see the spread of computer utilities, which, like present electric and telephone utilities, will service individual homes and offices across the country” [3,4].Grid computing systems[1,2] that have been the focus of much research movement in recent years supply a virtual skeleton for controlled sharing of resources across institutional limitations. Grid computing and its associated technologies will get popularity only if the users are made confident about their secrecy and the system must be as scalable, influential and faithful as of their own in their places. Resources selection and security guarantee are the two fundamental requirements in Grid applications.

Figure: A layered architecture for the computational Grid

Harmonized resource sharing and problem resolving in dynamic, multi institutional virtual organizations are the authentic and specific problems which emphasizes the concept of Grid. To make Grid computing more appealing, trust must be addressed and trust domains must exist where an entity can use resources or deploy services safely. Trust is a complex concept that has been addressed at different levels by many researchers [5, 6, 7, and 8].

II. TRUST

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Gambetta’s definition stresses that trust is vitally a belief or estimation, which has inspired the use of subjective logic as a way of measuring trust [22]. Castelfranchi and Falcone [21] extend Gambetta’s definition to include the notion of capability along with predictability. Trust is the organization of both human society and cyberspace security. Trust is not a black and white substance. Frequently grey area exists in conveying the trustworthiness of a computer site [23]. Like human relationship, trust is uttered by a linguistics term rather numerically. Trust differs with respect to time and situation .The idea of trust is a multipart subject related to a firm belief in attributes for instance dependability, uprightness and capability of the trusted entity. The trust definition is proposed by Farag Azzedin and Muthucumaru Maheswaran [24] is as follows: Trust is the firm belief in the competence of an entity to act as expected such that this Firm belief is not a fixed value associated with the entity but rather it is subject to the entity’s behavior and applies only within a specific context at a given time. The firm faith is a dynamic value and spans over a set of values ranging from very trustworthy to very untrustworthy. The trust factor is built on the basis of past experiences and has given for a specific context. The trust factor is specified within a given time since the trust level between two entities is not necessarily the same from at this time to a year ago.

There is a huge resource of information on the theory and application of trust, For instance [25], [26], [27], [28]. Trust has been documented as an significant characteristic of decision making for electronic commerce [29],[30] in the Internet world . The Grid Computing was initiated as a method of supporting scientific collaboration, where many of the participants knew each other sharing the resources. In this case, there is an understood trust relation, all partners have a common objective - for instance to realize a scientific experiment- and it is assumed that resources would be provided and used within some defined and respected boundaries. However, when the Grid is intended to be used for business purposes, it is necessary to share resources with unknown parties. Such interactions may involve some degree of risk since the resource user cannot distinguish between high and low quality resource providers on the Grid. The inefficiency resulting from this asymmetry of information can be mitigated through trust

mechanisms. Trust is specified in terms of a relation between a trust or, the subject that trusts a target entity, and a trustee, the entity that is trusted. Based on the relation between trust or and trustee, trust is classified into following categories [29]: Service Provision Trust, Resource Access Trust, Delegation Trust, Certification Trust, and Context Trust. In Service Provision, the trust or trusts the trustee to provide a service that does not involve access to the trust or’s resources. In Resource Access Trust, a trust or trusts a trustee to use resources that he own or controls. In Delegation Trust, a trust or trusts a trustee to make decisions on his behalf, with respect to a resource or service that the trust or owns or controls. Certification Trust is based on the certification of the trustworthiness of the trustee by a third party. Context Trust refers to the base context that the trust or must trust.

III. DIFFERENT CHALLENGES IN GRID COMPUTING

CHALLENGE 1: ABSENCE OF CLEAR STANDARD:

To facilitate mask the various features of different resources in grid environment, standard is the very first thing that needs to be invented[44]. From the starting of Global Grid Forum (GGF) [39], standard is the most important task for GGF. So far, Open Grid Systems Architecture (OGSA) [40][41] has been accepted however more and more voices from industries advocate Web Services Resource Framework (WSRF) [42]. Even though, there are still diverse tones for the future standards of grid computing. In absence of standard protocols, more and more grid applications will result in more supply centers.

CHALLENGE 2: CONFUSION ON THE SCOPE OF GRID

COMPUTING:

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Challenge 3: Grid application development is still difficult: The expansion of grid application tools is still very cumbersome though lots of research is going on in this field. Most of grid applications are implemented with the assist of computer scientists case by case.

CHALLENGE 4: SIGNIFICANT APPLICATIONS ARE LACKING:

Average size scientific computations are much easier and efficient to own and use a local super cluster. For extraordinary applications, such as global weather modeling and bioinformatics, a special designed super computer is needed, such as Earth-Simulator [32], Blue-Gene [33]. Because of the network latency and delay, a global super computer is not the most optimal resource in performance/price ratio. Mainly for data processing over the grid, it is much more cost-effective to build a data center other than using dataset remotely, as data storage is inexpensive than data transfer. Services computing [34][35] could be a possible killer application style for the future grid computing, as services are a much easier way to use than to own.

CHALLENGE 5: Lots of efforts should be done to make a software package or a service useable over grid One key resource for the researchers is existing software packages. Many existing software packages are running on dedicated platform, for example SMP cluster, or over a dedicated operating system. Every now and then it is very difficult to have them reusable over grid environment due to various reasons, such as lack of source code, copyright issues. Even though there are some software vendors who put their genuine efforts on this issue, such as Oracle 10g [36], this figure with grid-enable software packages is far behind the development of grid middleware.

CHALLENGE 6: CENTRALIZED MANAGEMENT RATHER

THAN LOCALIZED CONTROL

At present, most of grid computing projects are in centralized management scheme, which is due to two main reasons. The first reason is for most grid projects, participant organizations or institutions are limited, centralized management can be easily used to manage all the resources and services within a grid domain. The second reason is most grid middleware use “publish-find-bind” web services scheme [37]. The entire resources and services need to be registered to the Universal Discovery, Description and Integration (UDDI) center. This UDDI center becomes the central management point of grid system. This single domain scheme inhibits the scalability of grid entities joining the system, and also will be the single point of failure of the whole grid system. “China Grid Support Platform” (CGSP) [38] from China Grid project is a first step towards multi-domain web services architecture.

CHALLENGE 7: LACK OF SECURITY/TRUST BETWEEN

DIFFERENTSERVICES:

The grid requires a security infrastructure with the following characteristics: ease of use by users; conformation with the virtual organization security needs. The Grid Security Infrastructure (GSI) [4] GSI cannot easily achieve a common key for a virtual organization wide encrypted communication. Additionally, they do not have inherent means for realizing behavior control for a remote user and its client system environment. Such as consider that WS- security [23] can achieve message encryption between a resource provider and a user. On the other hand there is no way for a stakeholder in the resource provider to know whether or not the remote client environment is compromised (perhaps by a malicious code) even though it knows that such a compromise is equivalent to the nullification of the channel encryption service [24].

CHALLENGE 8: MANAGEMENT AND ADMINISTRATION OF

GRID IS THE MOST CHALLENGING ONE:

UK e- Science program [25] gives us a good example of how to setup national grid center and regional grid center, as well as some grid functional center, such as grid R&D center, grid support center, grid training center, grid software verification center etc.

IV. RELATED WORK THROUGH LITERATURE SURVEY

Our work is enthused by a number of previous works related to trust management and security enhancement for supporting Grid performance. These relate works are reviewed below.

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Vivekananth [11] proposed a behavior based trust model which shows the behavior conformity. In this model author concentrated on behavior of entities in diverse domains, in different contexts. The total trust will be calculated by direct trust and indirect trust. Both the trust will be evaluated by reputations. There will be tracking module, which will keep track of behavior. Based on experiences with the entities, an entity trust level will be increased or decreased. There can be a penalty factor, which can be levied for malicious behaviors. The trust factor between two Entities may depend on penalty, context and time. The penalty will be higher if the misbehavior creates heavy harm. Otherwise the penalty will be low. Based on this experience the trust will be updated. The penalty factor can be a number between 0 & 1. If the total trust is greater than the required trust then the resource is allocated. This model is still under revision.

Chuang Liu et al. [12] proposed a general-purpose resource selection framework by defining a resource selection service for locating Grid resources that match application requirements and evaluated them based on specified performance model and mapping strategies, and returned a suitable collection of resources, if any are available. Farag Azzedin and Muthucumaru Maheswaran [13] proposed a trust brokering system that operates in a peer to- peer manner. They have developed a security-aware model between resource providers and the consumers that separates the concepts of accuracy and honesty.

Shanshan Song et al. [14] proposed a new fuzzy-logic trust model for securing Grid resources. They have developed a SeGO scheduler for trusted Grid resource allocation. Wu Xiaonian et al [15] tried to quantify the entity’s trust according to the entity’s behaviors. This 67 behavior trust computation model is based on risk evaluation. This model includes asset identification, threat identification and trust relationship identification.

Woodas W.K. Lai et al [16] viewed trust in two aspects – identity trust and behavior trust. Issues on Grid context and trust tree structure are addressed to help in managing, evolving and interpreting trust.

Paul D Manuel et al [17] introduced a trust model to evaluate the Grid and cloud resources by means of resource broker. The resource broker chooses appropriate Grid/cloud resource in heterogeneous environment based on the requirements of user. This model considered metrics

suitable for both Grid and cloud resources. Trust enhanced resource broker evaluates the trust value of the resources based on the identity as well as behavioral trust.

Shashi Bhanwar et al [18] proposed a trust model for establishing and evaluating trust by computing reputation and trustworthiness of the transacting domain on the basis of number of past transactions and rated feedback score. The paper “Trust Cell: Towards the end to end Trustworthiness in data oriented Scientific Computing “by Sangmi Lee Pallickara, and Beth Plale. Suggests a trustworthy model between remote resources and participants. It uses trust cell, which is a set of resources, which are trusted and suggested with in the domain. One organization may put up one or more trust cells and a trust cell may consist more than one organization [19].

V. PROPOSED FOR TRUST BUILDING

In Grid computing, resource owners are often hesitant to enter the Grid environment because their valuable resources will be shared. This distrust leads many potential Grid entrants to use their own closed-box system rather a Grid system with other resources. There should be trust-based security solutions for sharing resources among participants. There should be a system of recommendation and trust calculation agent. Resources will be allowed to access by other participant if and only if a positive feedback is obtained from that dedicated agent.

VI. CONCLUSION

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REFERENCES

[1] I. Foster, C. Kesselman, and S. Tuecke, “The anatomy of the Grid: Enabling scalable virtual organizations,” Int’l Journal on Supercomputer

Applications, 2001.

[2] I. Foster and C. Kesselman (eds.), The Grid: Blueprint for a New

Computing Infrastructure, Morgan Kaufmann, San Fransisco, CA, 1999.

[3] Jeremy M. Norman (edited), From Gutenberg to the Internet: A Sourcebook on the History of Information Technology: 2005, pp. 870.

[4] L.Klienrock, “UCLA press

release,”1969,http://www.lk.cs.ucla.edu/LK/Bib/REPORT/press.html [5] A. J. Menezes, P. C. Oorshot, and S. A. Vanstone, Handbook of Applied

Cryptography, Fifth Edition, CRC Press, New York, 2001.

[6] C. Adams and S. Farral, “RFC2510 – Internet X.509 public key infrastructure certificate management protocols,” 1999.

[7] A. Abdul-Rahman and S. Hailes, “Supporting trust in virtual communities,” Hawaii Int’l Conference

on System Sciences, 2000.

[8] N. Damianou, N. Dulay, E. Lupu, and M. Sloman, “The Ponder policy specification language,” Workshop on Policies for Distributed Systems and Networks, 2001.

[9] R. Buyya and S. Venugopal, the Gridbus Toolkit for Service Oriented Grid and Utility Computing: An Overviewand Status Report, Proceedings of the First IEEE International Workshop on Grid Economics and Business Models (GECON), 2004.

[10] Renagaramanujam Srinivasan and Srivaramangai P. “A Comprehensive Trust Model for Improved Reliability in Grid.”, International Journal of

Computer Applications Volume5-No.7:1–4, August 2010. Published By

Foundation of Computer Science.

[11] Vivekananth.P “A Behavior Based Trust Model for Grid Security”, International Journal of Computer Applications (0975 – 8887) Volume 5– No.6, August 2010, Published by Foundation of Computer Science. [12] C. Liu, L. Yang, I. Foster and D. Angulo, “Design and Evaluation of a

Resource Selection Framework for Grid Applications”, in Proceedings of HPDC-11, 2002.

[13] F. Azzedin and M. Maheswaran, “A Trust Brokering System and Its Application to Resource Management in Public- Resource Grids”, in Proceedings of IPDPS 2004.

[14] S. Song, K. Hwang and M. Macwan, “Fuzzy Trust Integration for Security Enforcement in Grid Computing”, in Proceedings of IFIP International Conf. on Network and Parallel Computing, (NPC-2004), Wuhan, China, October 18–20, 2004, pp. 9–21.

[15] Wu Xiaonian; Zhang Runlian; Zhou Shengyuan; Ma Chunbo, “Behavior Trust Computation Model Based on Risk Evaluation in the Grid Environment”, WRI World Congress WCSE '09, 2009, Page(s): 392 – 396.

[16] Woods W.K. Lai, Kam-Wing Ng, Michael R Lyu, “Integrating Trust in Grid Computing Systems”, LNCS, vol.3251/2004, pg.887-890. [17] Manuel, P.D.; Thamarai Selvi, S.; Barr, M.I.A.- E., “Trust management

system for Grid and cloud resources”, First International Conference on Advanced Computing (ICAC)-2009, 2009, Page(s): 176 – 181. [18] Bhanwar, S.; Bawa, S, “Establishing and Evaluating Trust in a Grid

Environment”, 10th International Symposium ISPAN’09, 2009, Page(s): 674 – 678.

[19] Sangami Lcc Pallickaran, and Bcth Plalc “Trust Cell: Towards the End-to-End Trustworthiness in Data-oriented Scientific computing, “ in proceedings of the 2006 international conference on parallel processing workshops.

[20] D. Gambetta. Can We Trust Trust?

[21] C. Castelfranchi, R. Falcone. Principles of Trust for MAS: Cognitive Anatomy, Social Importance, and Quantification. In Y. Demazeau (editor), Proceedings of the Third International Conference on MultiAgent Systems. IEEE C.S., Los Alamitos, 1998.

[22] A. Josang. An Algebra for Assessing Trust in Certification Chains. In J. Kochmar (editor), Proceedings of the Network and Distributed Systems Security Symposium (NDSS’99). The Internet Society, 1999.

[23] Shanshan Song and Kai Hwang, Dynamic Grid Security with Trust Integration and Optimized Resource Allocation, Internet and Grid Computing Laboratory, University of Southern California, Los Angeles, CA. 90089 USA.

[24] Farag Azzedin, Muthucumaru Maheswaran, "Towards Trust-Aware Resource Management in Grid Computing Systems," ccGrid, p. 452, 2nd IEEE/ACM International Symposium on Cluster Computing and the Grid (CCGRID'02), 2002.

[25] C. Castelfranchi, R. Falcone, B. Sadighi, Y-H Tain. Guest Editorial. Applied Artificial Intelligence, 14(9), Taylor & Frances, 2000.[4] M. Waidner (editor). Ercim News, Special Theme: Information Security. No 49, 2002.

[26] M. Waidner (editor). Ercim News, Special Theme: Information Security. No 49, 2002.

[27] C.D. Jensen, S. Poslad, T. Dimitrakos (editors). Second International Conference on Trust Management. Lecture Notes in Computer Science, vol. 2995, Springer, 2004.

[28] P. Hermann, V. Issarny, S. Shue (editors). Third International Conference on Trust Management. Lecture Notes in Computer Science, vol. 3477, Springer, 2005.

[29] T. Grandison, M. Sloman. A Survey of Trust in Internet Applications. IEEE Communications Survey and Tutorials, 3, 2000.

[30] A. Josang, R. Ismail, C. Boyd. A Survey of Trust and Reputation Systems for Online Service Provision. Decision Support Systems, 43(2), pp 618-644, 2007.

[31] SETI@Home, http://setiathome.ssl.berkeley.edu/. [32] The Earth Simulator Center, http://www.es.jamstec.go.jp/. [33] The Blue Gene Project, http://www.research.ibm.com/bluegene/. [34] T. Erl, Service-Oriented Architecture: A Field Guide to Integrating

XML and Web Ser- vices, Prentice Hall PTR, 2004.

[35] IEEE Services Computing Community,

https://www.ieeecommunities.org/services.

[36] Oracle 10g, http://www.oracle.com/database/index.html.

[37] O. Zimmermann, M. R. Tomlinson, and S. Peuser, Perspectives on Web Services: Apply- ing SOAP, WSDL and UDDI to Real-World Projects, Springer, 2005.

[38] H. Jin, “ChinaGrid: Making Grid Computing a Reality”, Digital Libraries: International Collaboration and Cross-Fertilization - Lecture Notes in Computer Science, Vol.3334, Springer-Verlag, December 2004, pp.13-24.

[39] Global Grid Forum, http://www.ggf.org.

[40] Open Grid Services Architecture,

http://www.ggf.org/Public_Comment_Docs/Documents/draft-ggf-ogsa-specv1.pdf.

[41] S. Tuecke, Kzajkowski, I. Foster, J. Frey, S. Graham, C. Kesselman, D. Snelling, and P.Vanderbilt, Open Grid Services Infrastructure, February 17, 2003.

[42] K. Czajkowski, D. F. Ferguson, I. Foster, J. Frey, S. Graham, I. Sedukhin, D. Snelling, S.Tuecke, and W. Vambenepe, The WS-Resource Framework, http://www.globus.org/wsrf/

[43] I. Foster, C. Kesselman, and S. Tuecke, “The Anatomy of the Grid: Enabling Scalable Virtual Organizations”, International Journal of High Performance Computing Applications, 15 (3), 200- 222, 2001. [44] HaiJin, Huazhong University of Science and Technology, Wuhan,