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EVOLUTIONARY APPROACH TO ADDRESS THE NEGATIVE IMPACT OF SELFISH MAC BEHAVIOR ON RESOURCE AVAILABILITY IN M2M NETWORKS

The emergence of sophisticated applications has created a demand of diverse Quality of Service (QoS) requirement. Depending on the type of services provided by the application, the main concern of the wireless communication can shift from reliable transmission to high throughput delivery, stringent delay or vice versa. To cater for such QoS requirement, communication protocol such as IEEE 802.11ah and user programmable network interface card are introduced. Responsible for 70 percent (70%) of the performance of a network, modifications are introduced in Media Access Control (MAC) Layer of the protocol to improve the performance. These changes allow MAC parameters to be adjusted as needed for their respective QoS requirement. However, the dynamic tuning ability has changed the facet of resource contention for the conventional MAC protocol. The ability of tuning the MAC parameters at will has violated the fair share policy of conventional MAC parameters, and can be abused to gain individual benefit over the loss of other connected terminals in the associated network. This creates a security threat of resource availability in the network when connected terminals are denied their access to the radio resources, which is a case of Denial-of-Service (DoS). When a terminal tunes its parameter to gain personal benefit, this behavior is regarded as selfish behavior while terminal which tuned the parameter according to the standard are consider as behaving honestly. As the severity of selfish behavior intensify, the degree of effect of DoS for honest terminal will increase. In this work, we will analyze the interaction between terminals of different behavior using Evolutionary Game Theory. Using the framework from evolutionary game, the dynamic decision making and the change of behavior will be studied. A mechanism to discourage selfish behavior will be introduced towards the end of result analysis as a measure to enforce security for MAC layer in the network.

URL Reference: https://www.sciencedirect.com/science/article/pii/S1084804519302164

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JOURNAL
Title : Probability-based opportunity dynamic adaptation (PODA) of contention window for home M2M networks
Description :
With the emergence of the Internet of Things (IoT), the growing use of autonomous sensing and actuating devices in areas such as smart grid, e-healthcare, home networking, and machine-to-machine (M2M) communication has become an important communication paradigm. Nonetheless, to fully exploit the applications facilitated by M2M communication, service requirements such as data throughput, scalability and reliability must be in place. This paper proposes a new backoff adaptation mechanism known as probability-based opportunity dynamic adaptation (PODA) for M2M communication using the IEEE 802.11ah protocol. The proposed PODA is an enhanced version of the binary exponential backoff (BEB) where a station estimates the number of contending stations in a distributed manner and adaptively tunes its minimum contention window (CW) prior to the contention process for better network throughput and packet delivery ratio. Owing to its great flexibility and ease of implementation, BEB has been extended to home M2M communication such as wireless sensor networks and smart grid technologies without relying on wide area communication. However, the current form of BEB has its shortcomings in the emerging M2M paradigm. The adaptation of CW in PODA is based on the optimal station's access opportunity to improve network performance instead of direct CW scaling. Using the proposed adaptation method, the network throughput can be improved by as much as 18 percent in the home M2M network studied, while enhancing network reliability and fairness.
Authors : MOHD FADLEE BIN A RASID,ADUWATI BINTI SALI
Date Publish : 11/12/2019
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Fakulti Perubatan Dan Sains Kesihatan [25]
Fakulti Sains [18]
Fakulti Bioteknologi Dan Sains Biomolekul [6]
Fakulti Sains Komputer Dan Teknologi Maklumat [1]
Fakulti Bahasa Moden Dan Komunikasi [2]
Fakulti Kejuruteraan [2]
Institut Pertanian Tropika Dan Sekuriti Makanan [1]
Institut Gerontologi [2]
Institut Biosains [2]
Fakulti Sains Dan Teknologi Makanan [1]
Fakulti Ekonomi Dan Pengurusan [2]
Fakulti Perubatan Veterinar [4]
Fakulti Pertanian [8]
Fakulti Ekologi Manusia [2]
Institut Penyelidikan Produk Halal [1]
Institut Penyelidikan Matematik [1]
Fakulti Sains Pertanian Dan Makanan [2]
Institut Perhutanan Tropika Dan Produk Hutan [2]
Kampus Upm Bintulu [1]
Fakulti Perhutanan [6]

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Agricultural And Biological Sciences [13]
Biochemistry, Genetics And Molecular Biology [12]
Chemical Engineering [1]
Chemistry [11]
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Energy [4]
Engineering [3]
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Keyword

[M2M]