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K. Sindhu et al Int. Journal of Engineering Research and Applications ISSN : 2248-9622, Vol. 4, Issue 4( Version 2), April 2014, pp.14-20

RESEARCH ARTICLE

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Traffic Differentiation and Scheduling In Vehicular Sensor Network Using 802.15.4 K. Sindhu*, Dr. T. P. Saravanabava** *(Department of Embedded System Technologies, College of Engineering, Guindy, Chennai-25) ** (Deputy Director- Knowledge Data Centre, Anna University, Chennai-25) ABSTRACT The IEEE 802.15.4 is the widely used next generation standard protocol in many applications utilizing wireless sensor networks (WSN) especially in vehicular sensor network (VSN). However, currently differentiation and scheduling mechanisms are not provided in IEEE 802.15.4 specification to improve the quality of service (QOS) for delay sensitive and critical events. In this paper, multiple scheduling algorithms using FIFO, Priority queue, RED, WRR and DRR are integrated in compliance with IEEE 802.15.4 to improve the throughput, enhance bandwidth utilization rate, perform fast processing and delivery of urgent data traffic. NS2.35 has been used for simulating the VSN and different types of traffic like CBR, poisson and exponential traffic have been simulated. Keywords – Vehicular sensor network, scheduling, quality of service, differentiation, IEEE 802.15.4, zigbee.

I. INTRODUCTION Sensor networks are recently rapidly growing research area in wireless sensor networks. Wireless sensors are of small size and low cost are deployed to establish a sensor network. Vehicular networks are considered as mobile sensor networks and characterized by several basic and special characteristics such as no limited energy and storage capacity, high node mobility and fast topology changes. The vehicular sensor network can sense several types of data in its surrounding area to provide wide variety of services like traffic monitoring, crowded streets identifying, speed controlling, lost vehicle locating and environmental monitoring since it covers permanently a wide geographical area [1,2,3]. For wireless sensor networks (WSNs), IEEE 802.15.4 is used as de-facto standard. However, the behaviour of CSMA/CA results in collision at heavy load which reduces the throughput and energy consumption performance of WSN. These problems demand MAC layer solutions to be proposed to achieve the better performance of WSN. Scheduling aids in providing quality of service (QoS) support to the prioritized and categorized communication in wireless sensor networks.This research aims to enhance QoS in a Vehicular Sensor Networks (VSN) by integrating traffic differentiation and scheduling mechanisms in order to reduce the end-to-end delay, improve the throughput, enhance the bandwidth utilization rate and perform fast processing and delivery for urgent data traffic.. The rest of this paper is structured as www.ijera.com

follows. Section 2 gives a summary of related works and Section 3 gives a brief overview of service differentiation and prioritization methodology used in our scenario. Hence research constraints used by our model and generated simulation results are provided in Section 4. Finally, concluding remarks and future work are presented in Section 5.

II. PREVIOUS WORK The MAC layer includes a very important processing level. since it rules the sharing of the medium which affects the performance of all the upper layer protocols. MAC protocol support QoS provisioning and determining the QoS support performance by solving the medium sharing problems and reliable communication. [4] Proposed a service differentiation algorithm with slight modification on the protocol to enhance the achievement of slotted CSMA/CA for time-critical events. The service differentiation algorithms were particularly based on various parameters such as the macHinE, aMaxBE and the Contention Window (CW). They differently process the command and data frames since they are affected by high and low priority levels (service class), respectively. In other terms, different attributes have been defined and assigned for different service classes. This algorithm keeps slotted CSMA/CA in its original form and focuses on tuning related parameters effectively in keeping the criticality of messages. Some existing works [5,6,7] are interested in controlling over CW depending on the changes in the network status. In [5], the Sensing Back off Algorithm (SBA) has been addressed to maximize 14 | P a g e


K. Sindhu et al Int. Journal of Engineering Research and Applications ISSN : 2248-9622, Vol. 4, Issue 4( Version 1), April 2014, pp. channel throughput with impartial access to shared channel. When packet collision occurs, it multiplies its back off interval by α while on a successful transmission, both sending and receiving wireless sensors multiply their back off interval by β, and the others overhearing(sensing) a successful transmission decreases their back off intervals by θ. α, β and θ are defined in [5]. However, on the basis of p-persistent CSMA/CA protocol, [6,7] addresses dynamic IEEE 802.11 wireless networks. Their approaches assume having a precise number of the active wireless sensors, to estimate the network state, while they do not consider QoS for real-time traffic. [8] Uses CSMA/CA as access protocol to provide service differentiation in WSN. The Collect then Send burst Scheme (CoSenS) is developed to facilitate implementation of scheduling policies and primarily to handle its weaknesses. A earliest deadline first and fixed priority are implemented on the top of CoSenS. The results present that the proposed solution enhances reliability and end-to-end delay by adapting traffic variations automatically. Authors claim that proposed solution does not affect best effort traffic while meeting deadline requirements for urgent traffic. Moreover, motes are used for testing and implementation of CoSenS. Diff-MAC is a QoS aware MAC protocol based on CSMA/CA access method to support hybrid prioritization and differentiated services. Diff-MAC integrates an effective service differentiation algorithm in order to increase the channel utilization and provide fair and fast data delivery. Diff-MAC is needed in WSN supporting QoS-constrained heterogeneous traffic such as multimedia applications. To provide QoS, Diff-MAC consists of (1) Reducing the retransmission using fragmentation of the long frames into small manageable packets and transmitting them in form of burst, (2) Decreasing collisions and minimizing the packet latencies by adjusting its contention window size as per traffic requirements and (3) Providing fair and reliable data delivery among sensor nodes based on intra-queue prioritization feature [9]. In [10], author has proposed a system called VASNET (Vehicular Adhoc and Sensor Networks) which provides safety on highway roads, since many accidents and injuries have occurred due to car accidents. Two types of sensor nodes are suggested in VASNET, one is embedded inside the vehicle called Vehicular Nodes(VN) and other is deployed in predetermined intervals on roads called Road Side Sensor Nodes(RSS). There is a Base Station(BS) acts as police traffic station, firefighting group and rescue team. The VN collect the vehicles velocity and send it to BS via RSS. [11] Developed a novel cross-layer integrating an asynchronous Energy Efficient and www.ijera.com

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Fast Forwarding (EEFF) protocol for WSNs is resulting to energy efficiency and low latency. EEFF implements new approaches improving dynamic routing selection and low power listening which leads to reducing the latency. Node-based scheduling and level based scheduling, proposed in [12], are two centralized heuristic scheduling algorithms. The first algorithm is inspired from the classical multi-hop scheduling using direct scheduling of the nodes given in an ad hoc mode. The second algorithm uses a routing tree to schedule the levels before scheduling the nodes. This algorithm is more suitable for wireless sensor networks since it supports many-to-one communication model. A nodes distribution across levels affects the performance of these algorithms. In [13], the authors proposed at the MAC level a scheduling algorithm that is able to support assorted connections with different QoS necessities. At the physical (PRY) layer, each connection utilize an adaptive modulation and coding (AMC) scheme over wireless fading channels. The scheduling algorithm assigns a certain priority level based on the QoS requirements of each connection. Then, it adjusts dynamically the priority level according to the channel and service status. [14] Proposed a Real-Time Query Scheduling (RTQS) algorithm for conflict-free transmission scheduling in order to support real-time queries in WSNs. In this context, in conflict- free query scheduling [14] showed relatedness between prioritization and throughput. Then, it proposed nonpreemptive, preemptive and slack stealing query scheduling algorithms as novel approaches for realtime scheduling. As a result, the first algorithm achieves a better throughput by inverting priority. This problem has been solved by the second algorithm with trade-off of reduced throughput. Finally, the third algorithm combined the remuneration of preemptive and non-preemptive scheduling algorithms to improve the throughput and meet query targets. Current WSN applications generate different types of traffic with various requirements such as delay-bounded, bandwidth and reliable data delivery. Consequently, Quality- of-Service (QoS)-based mechanisms can improve efficiently the traffic delivery in WSNs. This work introduces new differentiated service approaches and tasks accomplished by scheduling disciplines and highlighting the impact of these techniques on the QoS support in mobile sensor networks.

III. SERVICE DIFFERENTIATION AND PRIORITIZATION METHODOLOGY Different types of traffic with various 15 | P a g e


K. Sindhu et al Int. Journal of Engineering Research and Applications ISSN : 2248-9622, Vol. 4, Issue 4( Version 1), April 2014, pp. requirements such as delay-bounded, bandwidth and reliable data delivery are generated. Consequently, Quality-of-Service (QoS)-based mechanisms can decrease end-to-end delay and improve efficiently the traffic delivery in a wireless sensor networks. We used differentiated service approach with scheduling mechanism to improve the overall network throughput. 3.1 PROBLEM FORMULATION A specific problem that arises as a result of the collected traffic diversity is how to differentiate and process the diversified traffic in a suitable way to their requirements. The traffic diversity is caused by multidisciplinary supported applications. It is controlled at the roadside unit (or base station) acting as routers and coordinators. Traffic diversity poses challenges that need to be resolved by integrating new mechanisms to (a) classify packets according to their types of service and (b) schedule them appropriately to their requirements. Grade of service is one of crucial parts of QoS in mobile communications which involves outage probability and blocking probability and scheduling starvation. Various mechanisms such as mobility management, fair scheduling, radio resource management, channel-dependent scheduling etc are affected to measure the above said performance measures. 3.2 POSSIBLE SOLUTIONS It includes the use of message relay boxes for collection, classification and scheduling messages and specific roadside gateways for proper data propagation. Moreover, maintaining Quality-ofService (QoS) in VSNs is challenging while nodes are mobile. IEEE 802.15.4 defines unslotted CSMA/CA channel access protocol which enables contending wireless sensors to access the shared channel without providing service differentiation at the MAC layer. This lack of providing service differentiation has hindered the development of service differentiation model for rate-sensitive applications. In this paper, a suitable scheduling scheme among various scheduler schemes is selected at MAC layer for assorted connections with varied QoS requirements. Therefore, a priority or weighted function is requested for every link established in the system and depending on wireless channel quality, service priority across layers and QoS satisfaction every connection is updated dynamically. The proposed scheduling model is flexible, scalable, easily implementable, guarantees QoS and utilizes the wireless bandwidth efficiently. MAC layer controls medium sharing and all upper layer protocols related to that for QoS provisioning. www.ijera.com

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QoS cannot be achieved at network, transport or higher layers without support of MAC protocol. The aim of this research consists of supporting Quality of Service (QoS) in a vehicular sensor environment by integrating traffic differentiation and scheduling mechanisms. To address QoS provisioning, the research uses the model of Service Differentiation. Service differentiation has two stages: (i) assigning priority, and (ii) differentiation between priority levels. The QoS is ensured using Queue Scheduling. A better performance is achieved by assigning appropriate priority to the traffic since higher priority is always served first. 3.3 DIFFERENTIATION IN VSN The first step for supporting Quality-ofService (QoS) in VSNs consists of including differentiation mechanism in theMAC layer, since several types of events with different significance and severity may happen in the roads. Moreover, other non-related road traffic is to be supported by the sensor network such as pollution control, urban application etc. The differentiation mechanism will not retransmit packets as they arrive but it consists of:  Collecting and classifying data from cars and other neighbor platforms  Marking and storing data in different queues characterized with different priority levels. 3.4 SCHEDULING IN VSN The scheduling in VSN is achieved and tested using the queuing methods such as FIFO, priority queue, RED, WRR, DRR. The proposed solution is evaluated by multiple scenarios using NS2.35 simulation. The simulation results show the proposed system improves the QoS when compared with standard system. The proposed system can achieve fast categorization of incoming traffic at RSU from the vehicles and treat them according to their prioritization assigned for each traffic type. The extensive simulation results further justify the usefulness of proposed system to get better QoS in VSN.

IV. SERVICE DIFFERENTIATION AND PRIORITIZATION 4.1 METHODOLOGY A low-cost and energy efficient IEEE 802.15.4 radio technology is used in nodes. These nodes communicate with road side units positioned over small distances along road side. In this simulation, FIFO, priority queue, RED, WRR, DRR scheduling algorithms are used to determine how quality of service can be enhanced. 4.2 RESEARCH CONSTRAINTS The research has been simulated using 16 | P a g e


K. Sindhu et al Int. Journal of Engineering Research and Applications ISSN : 2248-9622, Vol. 4, Issue 4( Version 1), April 2014, pp. NS2.35 on 6 lanes with 2 Coordinators and 4 Routers along the road. For simplicity, straight roads are considered and turns, comers and exits are omitted in our proposed high-way model. Each vehicle in the system is assumed to be equipped with a vehicle sensor system to send vehicle's information request to the RSU. For thorough testing the proposed scheme has been applied on packets of different sizes such as 500, 1024, 500, 2500 as shown in Table. 1It is assumed that vehicles running on the road with constant driving behaviors, such as lane change, acceleration, and overtaking, deceleration. Vehicles are moving in constant speed and moving in their lane. After the distance d1, d2, d3 is reached, the vehicle may wait for constant time period for signals on the road. Multiple scenarios are simulated concurrently and compared. PARAMETERS Transmission band

VALUES 2.4 Ghz

No.of routers

4

No. of coordinators

2

Traffic types

CBR, Poission, Exponential. 512, 1024, 1500,2500.

Packet size

Table 1 If mobile node is out of its parent transmission range, then it connects to the closer node and it continues with transmission. The network structure simulated using NS2.35 is shown in figure 1.

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shows the end-to-end delay result of the simulated scenario using differentiation and sheduling mechanisms. The DRR and WRR queue have less end-to-end delay as compared to others in this simulation.

Figure 2. End-end delay. 4.4 DELAY: Delay is measured when packets of data take more time than expected to reach destination. Figure 3 shows the measurement for overall global delay for FIFO, priority queue, RED, WRR and DRR scheduling schemes. Multiple factors contribute to delay such as network congestion and packet processing at each link till the final destination arrives. Their effects can be minimized by selecting a proper scheduling scheme. It is observed that DRR and WRR have a minimum values compared to RED, priority queue and FIFO. FIFO has the maximum delay as simulated in the scenario.

Figure 1. Network Scenario 4.3 END-TO-END DELAY End-to-end delay is used to measure network delay faced by every packet. It is measured as time interval from message transmission to the message complete delivery at receiving end. Figure 2 www.ijera.com

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K. Sindhu et al Int. Journal of Engineering Research and Applications ISSN : 2248-9622, Vol. 4, Issue 4( Version 1), April 2014, pp.

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Figure 3 Figure 4 4.5 DATA TRAFFIC SENT Data traffic sent is expressed as the total number of bits sent from source to destination per unit time. Data traffic sent includes all data bits irrespective of the condition whether these bits reach the destination or not. Figure 4 indicates the data traffic sent for FIFO, priority queue, RED, WRR and DRR scheduling schemes. It is noticed that data sent is maximum in case of DRR scheduling scheme as packets are held back those exceed from the packet length for the next round of scheduler. Those packets exceeds from packet length can be calculated by subtracting maximum packet size number from packet length. Also DRR scheduling scheme can handle variable packet size without knowledge of their mean size. It achieves a better generalized processor sharing (GPS) approximation without prior knowledge of mean packet size of each connection Also it has been noticed that data traffic sent is minimum in FIFO because it works as first in first out.

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4.6 DATA TRAFFIC RECEIVED Data traffic received can be expressed as "number of bits of the data received per unit time". Figure 5 depicts the data traffic received for the FIFO, priority queue, RED, WRR and DRR scheduling methodologies respectively in vehicular sensor network. It noticeably point out that the data traffic received is maximum in case of WRR scheduling scheme because each packet flow or connection has its own packet queue in a network interface card. WRR serves the amount of packets for every nonempty queue. Also it is noted that data traffic received is minimum in case of DRR scheduling scheme as packets are held back those exceed from the packet length for the next round of the scheduler. Those packets exceeds from packet length can be calculated by subtracting maximum packet size number from packet length. Although DRR scheduling scheme can handle variable packet size without knowledge of their mean size.

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K. Sindhu et al Int. Journal of Engineering Research and Applications ISSN : 2248-9622, Vol. 4, Issue 4( Version 1), April 2014, pp.

Figure 6

Figure 5 4.7 THROUGHPUT Throughput is the actual amount of data transmitted starting from the source to the destination within a given time (seconds). The importance of analyzing this QoS parameter is because the increased numbers of users of the wireless medium is the reason for increased possibility of interference. Throughput is quantified with various factors including packet collisions, barrier between nodes and the differentiation and scheduling mechanism used. It gives a general idea of the overall throughput of the system. Figure 6 shows that the maximum throughput is achieved using DRR scheduling mechanism, the WRR has second highest throughput and the priority queue has third highest throughput while FIFO and RED scheduling mechanism has the lowest throughput. The reason for this is because DRR scheduling mechanism is communicating more efficiently as compared to other mechanisms. Also in DRR mechanism distributed total load of the network among the ZigBee Routers as a result of which collisions and packet drops are decreased.

V. CONCLUSION This work introduces new differentiated service Approaches and tasks accomplished by scheduling disciplines and highlights the impact of these techniques on the QoS support in mobile sensor networks. We compared the use of different quality control algorithms for prioritizing and scheduling of traffic received from vehicles in ZigBee environment. On the basis of our measurements and results, DRR and WRR have increased QoS by decreasing the collision, packet drop rate and delay. This research can be further extended by implementing existing modern priority and scheduling mechanism or by presenting innovative new algorithm for particular scenario of vehicular sensor networks.

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