A Challenges In Manet Computer Science Essay

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The major challenges faced through the internet architecture inside incorporating rising wireless network elements such as mobile terminals, ad-hoc routers and embedded sensors and to provide end-to-end service abstractions so as to facilitate application development in imposed by Kavita T, et al.. The major challenges faced by the internet architecture can be broadly classified as:

a) Incorporating emerging wireless network elements such as MDs, ad-hoc routers and embedded sensors in the existing protocol framework.

b) To provide end-to-end service abstractions that facilitates application development.

These challenges are posed by a broad range of environments such as cellular data services, WiFi hot-spots, Info stations, mobile peer-to-peer, Adhoc mesh networks for broadband access, vehicular networks, sensor networks and pervasive systems. These wireless application scenarios lead to a diverse set of service requirements for the future Internet as summarized as:

1. Naming and addressing flexibility.

2. Mobility support for dynamic migration of end-users and network devices.

3. Location services that provide information on geographic position.

4. Self-organization and discovery for distributed control of network topology.

5. Security and privacy considerations for mobile nodes and open wireless channels.

6. Decentralized management for remote monitoring and control.

7. Cross-layer support for optimization of protocol performance.

8. Sensor network features such as aggregation, content routing and in-network Processing.

9. Cognitive radio support for networks with physical layer adaptation.

10. Economic incentives to encourage efficient sharing of resources.

A deep insight into three mechanisms to differentiate among traffic categories, i.e., differentiating the minimum contention window size, the Inter-Frame Spacing (IFS) and the length of the packet payload according to the priority of different traffic categories have been analyzed by Bo Li, et al. (2003). For that purpose an analysis model is proposed to compute the throughput and packet transmission delays. In order to gain a deeper insight into the modified IEEE 802.11 MAC with service differentiation support, system modeling and performance analysis are needed. The basic DCF method is not appropriate for handling multimedia traffic requiring guarantees about throughput and delay. For the quality of service of real-time multimedia it is important to know the time that a packet must wait for transmission over the IEEE 802.11 MAC. Because of this weakness, task group E of the IEEE 802.11 working group is currently working on an enhanced version of the standard called IEEE 802.11e. The goal of the extension is to provide a distributed access mechanism capable of service differentiation. By adopting the scheme of differentiating minimum contention window sizes and packet payloads of different traffic types, simple relationships exist among throughput and packet delays, which is helpful to simplify the design of the whole system. On the other hand, in order to make the system as simple as possible, one should limit the number of parameters that can be adjusted. On the whole, by using the analysis model proposed in this paper, one can obtain deeper insight, which is important and helpful to the design of real systems.

Extensive literature related to the performance analysis of the 802.11 MAC protocol in the ad hoc environment have been imposed by Giuseppe A, et al. (2003). The IEEE 802.11b extended version, also known as Wi-Fi, is the reference technology for ad hoc networking. The measurements were done in an outdoor environment, by considering different traffic types (i.e., TCP and UDP traffics). Experimental results indicate that transmission ranges are much shorter than previous version.

An analytical model to evaluate the IEEE 802.11 Distributed Coordination Function (DCF) saturation throughput performance was proposed by Bianchi G, et al. (2005). This approach relies on elementary conditional probability arguments rather than bidimensional Markov chains (as proposed in previous models), and can be easily extended to account for backoff operation more general than DCF’s one.

Wireless Local Area Networks (WLANs) has gained significant attention and revolutionized all over the world, because of its flexibility and does not require any cables for the implementation. IEEE 802.11 is the dominating protocol promoted by WLAN, which exemplifies specification of Medium Access Control (MAC) and physical layer (PHY). Based on the working principle of carrier sense multiple accesses with collision avoidance (CSMA/CA) scheme, IEEE 802.11 MAC protocol includes two modes like Distributed Coordination Function as mandatory and Point Coordination Function as optional for accessing channel. DCF lacks the differentiation mechanism between delay sensitive/insensitive real time traffic. Voice over IP and video come under delay sensitive real time traffic whereas FTP and e-main comes under delay insensitive traffic. On the other hand, PCF works on the fundamental principle of polling based contention free access scheme. This scheme employs access point as centralized control of point coordinator, which is mainly designed to reinforce applications like multimedia. Two techniques like two way handshaking (DATA-ACK), which provides basic access, and four way handshaking (RTS-CTS-DATA-ACK) that accommodates RTS/CTS data access is described by DCF for packet transmission. When the data transmission is initiated by basic access scheme, sender transmits the packet then the receiver responds the packet request and acknowledges the receiver by sending an ACK. In case of RTS/CTS scheme, short frame between transmitter and receiver is exchanged to reserve the channel and make the medium available for transferring short data packet.

The DCF scheme implemented by wireless station obtains the request for data transmission from upper layer. Based on the busy or idle status of the channel medium, station precedes the transmission and defer of data packets. This strategy avoids the probability of collision. A random backoff timer is generated by the station when the channel is busy. The transmission is deferred until idle DIFS is encountered, the timer value minimized in terms of slot time. If the counter reaches zero, then the station successfully transmits the packet. When the packet is delivered successfully at the destination node, it immediately waits for response of ACK and SIFS.

An analysis for probability of delay distribution in back off timer under saturation conditions is presented by Raptis P, et al. (2009). It is understandable that backoff timer elapse the time once after the successful transmission of packets. Author of this paper analyze the back off delay distribution and reported that all the stations should have packet for data transmission in WLAN under saturation conditions. The distribution of end to end delay algorithm is presented in a mixed scenario applicable to voice and data traffic. Another algorithm called admission control guarantees end to end delay and affords voice traffic. With the given probability distribution, algorithm for voice packets accomplishes end to end delay when the threshold value reaches low than the certain thresholds. Employing these algorithms assures low delay in most of the packet transmission.

IEEE 802.11 access method of DCF works on the basis of CSMA or CA protocol. Any of the station wants to establish the packet transmission, it first senses the channel. When the sensed channel is free then transmit the packet for a DIFS time otherwise station waits until the medium becomes idle. The channel starts the backoff process in terms of initializing the back off timer by producing a random value acquired from the uniform probability distribution in the parameter range of (0, CW-1). The obtained CW (Contention Window) value depends on the number of failed transmissions for the packet. The value of CWmin is used to set the CW value when attempting initial transmission and the value is doubled to the greatest of CWmax once after the transmission is unsuccessful. The values of CWmin and CWmax are fixed by the standard. When the proper delivery of packet to the destination is attained, ACK frame is send from the receiving station. Assumption of collision occurrence is made if the ACK frame is not delivered by the receiving station within an ACK timeout time. Once the collision is encountered, rescheduling of packet transmission is desired based on acquired backoff rules. Packet is discarded when the transmission count reaches beyond the limit of retry.

In IEEE 802.11, the mechanism of Request to Send or Clear to send is optional. The utilization of this option under the low range of back off timer, receiving station receives the RTS frame from the transmitting station. The receiving station responds the transmitting station by the CTS frame along with ACK frame at SIFS time.

1.12.5 RED CONGESTION CONTROL

For the accommodation of transient congestion in high speed network, gateways and large delay BW products are designed to manipulate greatest queues. In the current network scenario, TCP protocol encounters congestion when the packet is discarded at the gateway. To accomplish congestion avoidance an effective mechanism is employed at the gateway called RED (Random Early Detection), which supports transport protocols. One such algorithm was proposed by Sally Floyd, et al. (1993) that accomplishes the goal of avoiding bias against bursty traffic. In network, connection is established along the range of burstiness against traffic and Drop tail/Random drop gateways. In this paper, goal is twofold: One is to avoid bursty traffic and the other is deciding the connection that reduces the synchronization and avoids congestion. To surmount the problem of congestion avoidance and synchronization, distinct algorithm is used by gateways. Randomization technique is deployed by gateways to notify the packet arrival, which increases the probability of packet arrival rate of particular connection notification. This method is implemented in an efficient manner without manipulating the gateway connection state. Congestion avoidance gateway comprises the capability of reducing the average queue size. This method works by dropping the arrived packets when the queue size exceeds certain threshold value.

Akintola AA, et al. (2005) modified the original RED algorithm termed Dynamic Random Earlier Detection (DRED) algorithm based on a parameter named warning line, which was introduced by them. DRED was used to measure the burstiness of the traffic that was coming in, which was carried through computing the average queue size that was adjusted dynamically. Here, the scholars were highly interested and utilized the gateway in order to avoid congestions. In case there was a difficulty in obtaining the feedbacks from the gateway then the protocol that was implemented in the transport layer deduce the congestion through the following ways.

The computed service time of bottleneck

Changes in the throughput

Modification in end-to-end delay

Drop of packets

Queuing behavior of the packets in the nodes of the network can be viewed unfriendly only through the gateway. Moreover, gateway was shared through many connections that were active with delay tolerance, throughput requirement, roundtrip time, etc. The gateway was focused mainly to enhance the performance of end-to-end congestion control approach. Figure 1.6 shows the architecture of the proposed DRED mechanism.

Fig 1.6: Architecture of DRED

The results that were derived from various experiments showed that the DRED responded quickly as the number of packets has been increased at the gateway. It also represented that the performance of the DRED has improved on comparing with the standard RED congestion mechanism. This also helped to evade the overflow of buffers at the gateways.

Another queue based technique was proposed by Sharma V, et al. (2002) to modify the RED technique. The authors have studied the queue dynamics and provided stability, packet loss probability, rate of convergence, and waiting time distribution. These results were extended to a case where two traffic classes were present for each stream renewal. With this concept it was very difficult and computationally too expensive to measure the performance for a system. To overcome this, authors focused on approximating the dynamics preset in the average length of the queue through an ODE. Here they have considered a transient where the empty system began at time zero to receive the input stream. It was also used to explain a case where the input process differs in time. A special case was considered for the packets with exponential size distribution and arrival process in terms of Poisson that allowed deriving specific and accurate results.

Apart from that RED has a disadvantage towards parameter settings. This made it to perform poorly in the non-optimum parameter setting strategies. The dynamic changes in the network require the RED mechanism to optimize the parameter settings and dynamically updated. To overcome this, Vaidya, et al. (2006) proposed an optimized technique for optimizing the parameter settings. In addition to that, scholars also described a method that was model-free technique designed for tuning the parameters of RED, which do not need the knowledge about the conditions of a network, also it preserves the efficiency of model based optimized technique. The proposed technique was considered as a black-box. They have developed a gradient based two-timescale simultaneous robust stochastic approximation algorithm along with the deterministic perturbation sequence. Therefore, this approach does not require any explicit simulation of the network during analyzing through experiments. Furthermore, the experimental results presented in this article have determined that the optimized RED performed much better than the algorithm that were modified the standard RED mechanism for congestion control.

To analyze the drop behaviour of RED Wang Y, et al. (2004) proposed a complicated discrete-time queueing model. A matrix-analytic approach is applied to analyse both the long-term and the short-termdrop behaviour of a router with an RED scheme. The bursty nature of packet drop is examined by means of conditional statistics with respect to alternating congested and non-congested periods. The performance measures are derived by conditional statistics, including the long term drop probability, and the three short-term measures comprising average length of a congested period, average length of a non-congested period, and the conditional packet drop probability during a congested period. The packet stream is considered to follow a discrete-time batch Markovian arrival process (D-BMAP), and the queuing model of the router with an RED scheme can be modeled as D-BMAP/D/1/K. With a threshold level set in the RED scheme, the drop behavior of the D-BMAP/D/1/K queuing system with the RED scheme is characterized by examining the conditional statistics in a congested period and in a non-congested period through two hypothesized discrete-time absorbing Markov chains. Formulas are derived to explore the distributions of the lengths of a congested period and a non-congested period. In addition, the distribution of the number of packets dropped during a congested period and the long-term packet drop rate are evaluated.

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