Ahmad Kamal Bin Ramli

Profile

Academic Background 

  • Master in Computer Network ( MARA University of Technology, Malaysia )
  • Degree in Information Technology Hons ( Petronas University of Technology , Malaysia )

Working Background

Academic ( 6 Years )

  • Full Time Lecturer ( Nilai University , Unirazak University , Unitar International University)
  • Part Time Lecturer ( University Science Islamic of Malaysia , Tun Hussein Onn University , Open University of Malaysia)

Industrial ( 8 Years )

  • IT Manager
  • Senior System Enginneer
  • IT Coordinator / IT Head
  • Web Developer
  • Technical Consultant
  • System Analyst

Trainer 

  • Blackberry Developer
  • IPv6 
  • JAVA
  • Joomla
  • Drupal
  • Computer Forensics
  • Ethical Hacking

Professional Certificate

  • Certified Ethical Hackers ( CEH - EC-Council)
  • Certified IPv6 Engineer Level 1 ( Ipv6 Forum)

Research interests

Overview of My Resarch 

Internet access is the vital catalyst for online users, and the number of mobile subscribers is predicted to grow from 6.7 Billion in Q2 2013 to 9.3 Billion by the year 2019 [1]. To ensure demand is within the bandwidth capacity of current Internet Service Providers (ISPs), a mechanism is needed to ensure user satisfaction for their services. An ISP has the opportunity of getting more revenue by imposing an extra cost for services through peering inter domain networks such as metro Ethernet, Enhanced Interior Gateway Routing Protocol (EIGRP) and Border Gateway Protocol (BGP). However, ISPs have their own limitations such as tiers, available bandwidth and business models to serve current, potential end users, and corporate customers. This scenario leads to an ongoing market price issue and at present there is no concrete solution to undertake that effectively. To streamline the existing architecture running on private or public networks [2], an adaptive solution regarding the policies of getting the right agreement and negotiation in decision making must be available within the ISPs neighbourhood or inter domain networks. An adaptive architecture inspired by autonomic computing will ensure the process is transparent between autonomic elements in inter-domain operations. The key to this architecture is the extension of self - * capabilities [3] designed to have self-management over user behaviour, available network resources and interactions with neighbouring ISPs [4].

This enterprise feature is considered, to some extent, in organic computing, Autonomous Software Defined Networking (ASDN), Software Defined Networking (SDN) and will address the problem statement between inter ISPs services. A Service Level Agreement (SLA), is the utmost legal catalyst to monitor any contract violation between both end users and ISPs and is embedded with Quality of Service (QoS). It will strengthen and advance the quality of control over the application and network resources and can be further stretched out by leveraging into ensuring permitted time in mission-critical applications, better user experience and manage the costs of the resources efficiently. A broker is a matchmaker between ISP to get the best offer on their services with series of negotiation over each SLA towards the agreement. This is a onetime approach and there is no available mechanism for the continuous monitoring on any violation of the agreement. A manual renegotiation process between ISP has to be established to discuss the penalties or a new offer over the agreed SLA. With that, an adaptive framework with a broker as the virtual provider will be an excessive contribution to this research to overcome the manual process and establish a thorough monitoring and penalties on the agreed SLA.

A considerable amount of literature has been published on the development of autonomous approaches [5], [6] and inter domain architecture [7], [8]. However, little attention is given to self-management features with the Monitor, Analyse, Plan and Execute (MAPE) Model [3] to support the services running through inter ISPs environments. Recently, an adaptive framework for link prices at the maximum of two ISPs and inter ISP connection using agents rather than autonomic elements was proposed. As for industrial environments, CISCO proposed Application Centric Architecture [9], a robust approach and limited to the local network and is famously known within Software Defined Networking (SDN). Lastly, Autonomic IT Management as a service for cloud computing is presented in [10] but left the inter domain architectures with fully autonomic computing framework [11] for further investigation.

References

[1] I. Update, O. N. The, P. Of, and T. H. E. Networked, “Mobility Report,” no. February, pp. 4–7, 2013.

[2] A. Lodhi, N. Larson, A. Dhamdhere, C. Dovrolis, and R. Teixeira, “Using PeeringDB to Understand the Internet Peering Ecosystem,” ACM SIGCOMM Comput. Commun. Rev., vol. 44, no. 2, pp. 20–27, 2014.

[3] K. Ahuja and H. Dangey, “Autonomic Computing: An emerging perspective and issues,” 2014 Int. Conf. Issues Challenges Intell. Comput. Tech., pp. 471–475, Feb. 2014.

[4] S. Jordan, “How Do ISP Data Caps Affect Subscribers ?,” pp. 1–20, 2013.

[5] R. M. Bahati and M. a. Bauer, “An Adaptive Reinforcement Learning Approach to Policy-Driven Autonomic Management,” 2009 Fifth Int. Conf. Auton. Auton. Syst., pp. 135–141, 2009.

[6] a. Kertesz, G. Kecskemeti, and I. Brandic, “An interoperable and self-adaptive approach for SLA-based service virtualization in heterogeneous Cloud environments,” Futur. Gener. Comput. Syst., vol. 32, pp. 54–68, Mar. 2014.

[7] U. Computing, “A PPLICATION OF A UTONOMIC C OMPUTING,” pp. 203–208, 2012.

[8] R. M. Bahati and M. a. Bauer, “Adapting to Run-Time Changes in Policies Driving Autonomic Management,” Fourth Int. Conf. Auton. Auton. Syst., pp. 88–93, Mar. 2008.

[9] Cisco, “Cisco Application Centric Infrastructure,” pp. 2014–2016, 2013.

[10] V. T. O. Reality, “Autonomic and Cognitive solutions Imagine a more efficient world.”

[11] P. Vrancx, P. Gurzi, and V. U. Brussel, “A Reinforcement Learning Approach for Interdomain Routing with Link Prices,” vol. 10, no. 1, pp. 1–26, 2015.

Qualifications

  • Master In Computer Network
  • Degree In Information Technology (Hons)

Publications:

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