DEVELOPING QOS BY PRIORITY ROUTING FOR REAL TIME DATA IN INTERNET OF THINGS (IOT) URBAN SCENARIOS
Radwan S. Abujassar, Arab Open University, Kuwait
In networks, many application protocols such as CoAP, REST, XMPP ,AMQP have been proposed for IoT communication which includes p2p or S2S. In MANET Network convergence does the way for improvements in Internet of Things (IoT) communication with high potential for a wide range of applications. Each protocol focuses on some aspects of communication in the IoT. Hence, these application protocols have indicated of how IoT has integrated to enhanced and developed of a new service that require to guarantees the wide range offered by the quality of services. In this paper, we will introduce a smart pathway that can be bridge the gap between IoT services with its real data traffic. Therefore, we enhanced the MANET routing protocol for computing two or more paths to pass the more that one high priority real traffic data via these paths to improve the gloomy picture of this protocol in the context of IoT. In particular, the good services with high timely delivery of urgent data such as real time data environmental monitoring. After surveying the published and available protocol interoperability given for urban sensing. In this research, we have proposed a novel solution to integrate MANET overlays, and collaboratively formed over MANET, to boost urban data in IoT. Overlays are used to dynamic differentiate and fasten the delivery of high priority real application time data over low-latency MANET paths by integrating with the original specifications. Our experimental results showed the effectiveness on the network such as the overhead and network congestion. In addition, the initial results of the light-weight improved the routing protocol over the baseline protocols in terms of the delay of receiving the packets between nodes which lead to increase the throughput by reducing loss packets
Quality of Service (QoS), Adhoc on demand Distance Vector Alternative (ODVA), Open Link State Routing (OLSR), Internet Of Thing (IOT)
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http://aircconline.com/ijcnc/V11N6/11619cnc03.pdf
CONTEXT-AWARE ENERGY CONSERVING ROUTING ALGORITHM FOR INTERNET OF THINGS
D. Kothandaraman1 ,C. Chellappan2,P. Sivasankar3and Syed Nawaz Pasha1 , 1S R Engineering College, Warangal,India , 2Anna University,India , 3NITTTR,India
Internet of Things (IoT) is the fast- growing technology, mostly used in smart mobile devices such as notebooks, tablets, personal digital assistants (PDA), smart phones, etc. Due to its dynamic nature and the limited battery power of the IoT enabled smart mobile nodes, the communication links between intermediate relay nodes may fail frequently, thus affecting the routing performance of the network and also the availability of the nodes. Existing algorithm does not concentrate about communication links and battery power/energy, but these node links are a very important factor for improving the quality of routing in IoT. In this paper, Context-aware Energy Conserving Algorithm for routing (CECA) was proposed which employs QoS routing metrics like Inter-Meeting Time and residual energy and has been applied to IoT enabled smart mobile devices using different technologies with different microcontroller which resulted in an increased network lifetime, throughput and reduced control overhead and the end to end delay. Simulation results show that, with respect to the speed of the mobile nodes from 2 to 10m/s, CECA increases the network lifetime, thereby increasing the average residual energy by 11.1% and increasing throughput there by reduces the average end to end delay by 14.1% over the Energy-Efficient Probabilistic Routing (EEPR) algorithm. With respect to the number of nodes increases from 10 to 100 nodes, CECA algorithms increase the average residual energy by16.1 % reduces the average end to end delay by 15.9% and control overhead by 23.7% over the existing EEPR..
Energy conserving, smart mobile devices, Routing, Residual energy, Inter-meeting time.
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http://aircconline.com/ijcnc/V11N3/11319cnc02.pdf
FAST PACKETS DELIVERY TECHNIQUES FOR URGENT PACKETS IN EMERGENCY APPLICATIONS OF INTERNET OF THINGS
Fawaz Alassery , Taif University, Taif, Saudi Arabia
Internet of Things (IoT) has been receiving a lot of interest around the world in academia, industry and telecommunication organizations. In IoT, many constrained devices can communicate with each other which generate a huge number of transferred packets. These packets have different priorities based on the applications which are supported by IoT technology. Emergency applications such as calling an ambulance in a car accident scenario need fast and reliable packets delivery in order to receive an immediate response from a service provider. When a client sends his request with specific requirements, fast and reliable return contents (packets) should be fulfilled, otherwise, the network resources may be wasted and undesirable circumstances may be counted. Content-Centric Networking (CCN) has become a promising network paradigm that satisfies the requirements of fast packets delivery for emergency applications of IoT. In this paper, we propose fast packets delivery techniques based on CCN for IoT environment, these techniques are suitable for urgent packets in emergency applications that need fast delivery. The simulation results show how the proposed techniques can achieve high throughput, a large number of request messages, fast response time and a low number of lost packets in comparison with the normal CCN.
Internet of Things, Content-Centric Networking, emergency applications, data delivery, real-time packets.
For More Details :
http://aircconline.com/ijcnc/V11N3/11319cnc03.pdf
A MARKOVIAN MODEL FOR INTERNET OF THINGS APPLICATION
Osama Salameh and Mohammed Awadand Fadi AbuAlrub , Arab American University, Palestine
Internet of Things (IoT) allows communication among human-to-things, things-to-human, and things-to things that are incorporated into an information networks allowing automatic information interchange and the processing of data at real time. In this paper, we conduct a performance analysis of a real application defined through four traffic classes with the priorities present in smart cities using Continuous Time Markov Chains(CTMC). Based on a finite capacity queuing system, we propose a new cost-effective analytical model with a push-out management scheme in favor of the highest priority (emergency) traffic Based on the analytical model, several performance measures for different traffic classes have been studied extensively including blocking probability; push out probability, delay, channel utilization as well as overall system performance.
Performance analysis, Markov chain, IoT.
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http://aircconline.com/ijcnc/V11N2/11219cnc08.pdf
HISTOGRAM OF NEIGHBORHOOD TRIPARTITE AUTHENTICATION WITH FINGERPRINT-BASED BIOMETRICS FOR IOT SERVICES
S. Kanchana , PSG College of Arts & Science, Coimbatore, India
Internet of Things (IoT) and services is an interesting topic with a wide range of potential applications like smart home systems, health care, telemedicine, and intelligent transportation. Traditionally, key agreement schemes have been evaluated to access IoT services which are highly susceptible to security. Recently, Biometric-based authentication is also used to access IoT services and devices. They are involving a larger amount of memory with increased running time and found to be computationally infeasible. To provide robust authentication for IoT services, Histogram of Neighborhood Tripartite Authentication with Fingerprint Biometrics (HNTA-FB) for IoT services is proposed in this paper. This proposed HNTA-FB method uses binary patterns and a histogram of features to extract the region of interest. To reduce the memory requirements while providing access to IoT services, Histogram of Neighborhood Binary Pattern Pre-processing (HNBPP) model is proposed. The discriminative power of Neighbourhood Binary Pattern Registration (NBPR) is integrated with the normalized sparse representation based on the histogram. Additionally, this work presents a new Tripartite User Authentication model for fingerprint biometric template matching process. When compared with different state-of-the-art methods, the proposed method depicts significantly improved performance in terms of matching accuracy, computational overhead and execution speed and is highly effective in delivering smart home services.
Binary Patterns, Fingerprint Biometrics, Histogram, Internet of Things, Neighborhood Tripartite Authentication.
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http://aircconline.com/ijcnc/V11N5/11519cnc02.pdf
QOS CATEGORIES ACTIVENESS-AWARE ADAPTIVE EDCA ALGORITHM FOR DENSE IOT NETWORKS
Mohammed A. Salem1,Ibrahim F. Tarrad2,Mohamed I. Youssef 3 and Sherine M. Abd El-Kader3 , 1 Higher Technological Institute, Egypt , 2Al-Azhar University, Cairo, Egypt , 3 Electronics Research Institute, Giza, Egypt
IEEE 802.11 networks have a great role to play in supporting and deploying of the Internet of Things (IoT). The realization of IoT depends on the ability of the network to handle a massive number of stations and transmissions and to support Quality of Service (QoS). IEEE 802.11 networks enable the QoS by applying the Enhanced Distributed Channel Access (EDCA) with static parameters regardless of existing network capacity or which Access Category (AC) of QoS is already active. Our objective in this paper is to improve the efficiency of the uplink access in 802.11 networks; therefore we proposed an algorithm called QoS Categories Activeness-Aware Adaptive EDCA Algorithm (QCAAAE) which adapts Contention Window (CW) size, and Arbitration Inter-Frame Space Number (AIFSN) values depending on the number of associated Stations (STAs) and considering the presence of each AC. For different traffic scenarios, the simulation results confirm the outperformance of the proposed algorithm in terms of throughput (increased on average 23%) and retransmission attempts rate (decreased on average 47%) considering acceptable delay for sensitive delay services.
IoT, IEEE 802.11, EDCA, CW, AIFSN, MAC, QoS
For More Details :
http://aircconline.com/ijcnc/V11N3/11319cnc05.pdf