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Static Route Versus Dynamic Channel Allocation Systems Computer Technology Essay

Abstract- Channel Allocation Strategies have always presented a essential role in achieving better performance of cellular networks. This newspaper has researched the evaluation between two of the very most known techniques of channel allocation specifically: Static Channel Allocation and Dynamic Route Allocation. The contrast is made over two types of sites sole radio network, in which each of cordless node has only 1 radio user interface, and multi radio network, where each one of the node has at least two transceivers. This paper presents the detail survey of all existing evaluation made between both of these schemes.

Keywords- Route Allocation Scheme, Dynamic Route Allocation, Static Channel Allocation, Sole radio network, Multi-radio network

Introduction

Growth in the customers of the cellular networks, let it be cellular systems or any other Cellular network, has amplified the need to have the systems which can have significantly more capacity and hold more and more users. Enhancement of cordless market has made capacity of the cellular network a scarce learning resource. Solutions to improve effective capacity usage of the cordless network are in mind and in [4], it is noticed these methods entail source coding techniques, electric power control, better modulation schemes, advanced antennas. Other then these methods capacity of wireless system can be improved by setting up more bas channels i. e increasing number of transmitting equipment or improving hardware equipment of current system. Using better route allocation plans is also one of the techniques to improve capacity utilization of cordless network.

The goal of this newspaper is to give attention to channel allocation schemes. These route allocation schemes are not a lot of importance in the wired networks because their topology is secure plus they do not offer any flexibility to the users/nodes. But in the wireless networks, route allocation of key importance. The essential role of the cellular networks is the fact that they offer mobility to users hence, the route allocation algorithm must assign channels to ports and portables so that best trade-off between your quality of service and system performance is managed [3].

A given spectrum of consistency, can be divided into several independent collections, these independent sets are completely disjoint with each other. Hence even if they are used simultaneously, they'll not interfere with one another. So splitting the consistency spectrum into self-employed channels and then using all the programs for communication simultaneously present improvement in the capacity utilization [6].

The channel allocation strategy is known as to be the central of mobile networks because it not only affects the product quality and the availability of the programs to the user but changes the syndication of the traffic and hence, overall shapes the capability of the network [3].

Two of the most typical channel allocation techniques are believed in this paper namely, FCA- Fixed Channel Assignment or Fixed Channel Allocation and DCA- Vibrant Route Allocation.

Fixed Route Allocation (FCA)

Fixed Channel Allocation is also called Static Route Allocation. It really is known as Fixed or Static because once the channel is assigned to a dock or a user it generally does not change for the complete course of procedure. It can be used in all TDMA/FDMA digital mobile mobile sites [5] as number of frequency carriers in each cell stays fixed and does not depend on traffic load. It really is a period insensitive solution, as with the passage of time allocation of the channels to nodes does not change. Although in real-time, traffic load in a cell varies, there are peak hours when the traffic load grows to to almost 100% and then there are tranquil hours in a cell when traffic load is suprisingly low. This limitation dispirits the use of the FCA. But if a static condition is known as there is most probably an opportunity to get good performance with this route allocation algorithm [3].

In a mobile system predicated on the FCA, stations are partitioned among the list of cells permanently so that if all the skin cells use all the programs designated to them together, you will see no interference [1].

Figure - cell style for Static Channel Allocation with N = 7

With more complex systems other channel strategies can perform higher efficiency however they require processors with more memory. But it can be an essential sacrifice to make such as [4] it is mentioned that in each cell there are no static conditions, space traffic imbalance varies from 10% to 70%, which imbalance in the traffic depends on the size of the cell or service area and type of the surroundings, whether its metropolitan, suburban or rural area [4].

Dynamic Route Allocation (DCA)

In DCA, occurrence channels aren't fixed for any node or consumer. Depending upon familiarity with the environment, programs are allocated to the user. The syndication of the frequency companies in a cell will depend on upon syndication of the users/nodes in the cell and also on offered traffic insert. DCA happens to be reinforced by the GSM [5]. In Active Channel Allocation Scheme all the programs which are available for a system, are held in a queue or a spool. These stations are assigned to any cell briefly. Really the only constraint is to fulfil the distance standards, so that interference can be minimized [2].

The existing plans for the Active Route Allocation can be grouped into three main types: IA-DCA (Disturbance Adaptive Dynamic Channel Allocation), LA-DCA (Location Adaptive Dynamic Route Allocation) and TA-DCA (Traffic Adaptive Active Route Allocation), these strategies are based on the sort of network dynamics they consider while making decision [4]. All DCA strategies basically evaluate the price tag on using each available channel and opts the channel which introduces lowest cost [2].

For most accurate and good decision for route allocation, the algorithm should have accurate understanding of the surroundings [3]. The primary algorithms which are considered under the analysis of Dynamic Route Allocation are: DCET, Bellcore and Segregation DCA [3]. In DCET and Bellcore DCA algorithms, the decision of route allocation is based on only single dimension of route dynamics, within the Segregation DCA, a radio program acquires the route depending after its learning through earlier experience of route usage. With the past knowledge, channel which has highest probability of success is chosen for operation. Although this algorithm requires processors with memory space yet as decision is more meaningful so its performance is preferable to the DCET and Bellcore DCA algorithms [3].

In figure 2, in [7] results of performance of different kind of DCA schemes are likened.

Figure - Performance of Different DCA methods

Section II of the paper compares both of the channel allocation schemes in a single radio network and Section III shares the evaluation done of route allocation schemes in multi-radio network. Section IV stocks the identified regions where future work can be done and Section V concludes the paper.

Comparison of DCA and FCA in Single Radio Network

A single radio network a network where every one of the nodes of the wireless network consist of maximum of 1 radio interface and this single radio software is used for the communication purposes. With this section the comparability of the DCA and FCA in solitary radio network is presented.

Figure - Algorithms for Dynamic Channel Allocation

In a given cell, in case a node requests a call, it'll be served only and only when the cell has an unused route available, which fulfils the reuse standards, otherwise the call will be clogged [1]. Such is the situation with Static Channel Allocation Structure. But this isn't the case with the Active Channel Allocation Techniques, as for every of the decision that is to be served; route is taken from the overall pool that holds all the programs available for cellular system.

In any route allocation strategy, primary goal is for the best possible way to reuse the programs to increase the systems' capacity, while keeping interference in the machine at minimum and provide quality of service to an individual [4]. From another view, for allocating channel, the objective is taken concerning allocate the route to a call so that quantity of blocked cell phone calls is minimized and the amount of dropped phone calls is also reduced. In the end, the route allocation scheme locates the best trade-off between both of these aims because generally concern is directed at minimize the amount of dropped cell phone calls, as having a call lowered is more unwanted then devoid of the call linked by any means [1].

Both strategies for route allocation FCA and DCA are likened under the assumption that the call arrival circulation is Poisson [5]. For the purpose of modelling in FCA it is considered that we now have z numbers of channels per frequency carrier and y is the number of control programs. In confirmed cell i, let final number of regularity carrier be Ci and the total number of channels in the cell, which will be used to provide a call will be ci. The manifestation for ci is given as:

(1)

While this will not be the situation for DCA, as regularity carriers aren't permanently designated to the cell. As the route assignment depends on environment so, if we take n as the number of active calls in any cell, then regularity carriers allocated to that cell will be:

(2)

Total range of channels required, for just about any cell should be equal to the number of active calls and the control stations. But the volume of frequency carriers which includes z amount of channels each should be either more or identical than actually required [5].

In equation (2), implies that value is always taken similar or greater than "a" [5].

For the first simulation, the entrance rate of the telephone calls is defined at the overload value; which means that the overload period is considered where the numbers of calls initiated per minute tend to be than the genuine capacity of the machine.

The observation made over here's that, under heavy traffic fill, efficiency of the network or the channel utilization and capacity of the network will not improve by using DCA rather than FCA. Although it was regarded as the fact that DCA will usually perform much better than FCA.

Figure - Effect of the handover on FCA and DCA

In physique 4, the trend observed is known as trend of low capacity island [5]. Under heavy load, no profit is attained by using DCA, as in such a scenario both of the schemes will be utilizing capacity to the full extent. Somewhat DCA may perform worse than FCA. The reason is that scheduled to dynamic route allocation, a cell may acquire a few of the frequency stations form the neighbouring skin cells during the low traffic period and the neighbouring cell will not get the route back. The cell which has obtained the channel is why don't we say known as the blessed cell, and the cell which donated the route and in the end, was struggling to get it again is recognized as unlucky cell [5]. Now during the high fill traffic period, if blessed cell wants to handover the decision to a neighbouring unlucky cell. But as the unlucky cell would already be out of available programs to have the ability to serve the decision, call will be fell. Hence under such a scenario the drop out possibility of dynamic channel allocation system would be greater than static route allocation algorithm.

Other simulation is to determine the result of the appearance rate on call blocking probability. Appearance rate is the number of calls initiated per minute.

Through simulation, it is figured DCA performed better if the traffic weight is within the number 0. 6 to 0. 9 Erlang/BS/Channel. (body 5)

Figure - Examination of DCA and FCA, call obstructing ratio with respect to the appearance rate of the calls

During the next circumstance it was considered that entrance rate is Poisson and the other variables like handover rate and call positioning time etc are consistently distributed all around the cell.

From the amount 6 it is clear that as probability of call blocking boosts with the upsurge in the entrance rate of telephone calls. Which is rather obvious, more will be the variety of the users which are to be served, there is certainly more likely the opportunity that a few of them might not be able to get a free route.

Figure - Performance examination of FCA and DCA, Arrival rate of phone calls with regards to the over all preventing probability

Under such consideration as can be viewed from the body 6, DCA does much better than FCA, as in case of congestion in a cell, DCA can acquire stations from the neighbouring skin cells but in case of FCA, the scheme does not have any option but to reject the oncoming calls in case there is congestion.

Figure 7 shows the quantity of traffic carried by FCA and DCA in line with the traffic load.

Figure - comparability between FCA and DCA with regards to the carried traffic under the traffic load

Figure 8 shows the performance of the route allocation schemes when traffic imbalance is known as. It is discovered that network capacity to carry data, in case there is FCA, reduces significantly when data imbalance is considered. But in circumstance of DCA, there is no significant degradation in systems capacity to transport the data. There is also significant increase in the number of calls obstructed by FCA, due to increase in the traffic imbalance. But as the transported capacity does not decrease much in case there is the DCA, there is not much of the increment in variety of the blocked telephone calls.

Figure - FCA Vs. DCA, effect of the traffic imbalance on the both route allocation techniques

Comparison of DCA and FCA in Multi Radio Network

A multi radio network is the sort of the network where each node has at least several than two transceivers.

Fixed Channel Allocation in Multi-radio network

It is pointed out in [14], throughput and overall performance of wireless systems decreases with increased density of radios, but major reason behind this issue is these radios do not transmit the data all together as the nodes are generally configured with sole radios only and this factor basically limits the forwarding capacity of the network. In [15], the creators have emphasized that with the launch of more than one NIC (Network user interface cards) in wireless systems, performance of the system can be improved upon 6 to 7 times, rather than just doubling the performance. The same happening has been established in [16].

There has been much work done, in which the performance gain in cordless mesh sites with multiple interfaces is discussed when compared with single radio program network. In [13], capacity gain between solo radio, dual radio and multi-radio wireless mesh systems is compared and realistically the gain achieved by having multiple radio interfaces in the network has been reviewed.

Apart from that, in [17], creators have suggested that with execution of multi-radio Diversity approximately 2. three times performance gain is assessed in the solitary radio network.

Under the multi-radio scenario, one essential aspect is to consider proper channel assignment. Each one of the radios should be tuned to a occurrence through which the throughput of the complete network is maximized. The advantages of multiple radios is not minus the trade from increased difficulty of channel project techniques and the traffic allocation methods [20] and apart from that, more work is done in this domain. In [10], [8], [19], the writers have suggested some methods to get maximum possible throughput by different route task algorithms.

The idea of the Static Channel Allocation in this section is prolonged to Cellular Mesh Systems, as before the start of the operation in the cordless mesh networks the channels are properly allocated and then till the finish of the procedure, the channel task will not change. With this section, multi-radio wireless mesh network is considered and it is seen that how by having multiple radio interfaces the performance of the network helps.

Figure - Performance of the FCA algorithms with 3 channels

Figure 9 shows the impact of the various algorithms for the route allocation in the three channel program [8].

Figure - performance of the FCA algorithms with 12 channels

Figure 10 shows the impact of different algorithms for the route allocation in the twelve route structure [8].

Figure 11 shows that with different channel allocation algorithms, how the increment in quantity of interfaces per node impacts the performance of network. In all algorithms it is detected that with the upsurge in volume of radio interfaces per node, throughput of cellular networks enhances [9].

Figure - FCA algorithm comparison with different amount of radio interfaces per node

Figure - effect of increased quantity of interfaces per node on the over-all normalized broadcast latency

In figure 12, it is shown that with different route allocation techniques for multi-interface cellular mesh network, normalized latency for broadcast lowers with the upsurge in number of radio interfaces per node [9].

In shape 13, it is simulated that with the increase in the amount of interfaces per node, there is not an infinite increment in capacity usage. Multi radios are being used so that in a network there may be as much concurrent transmissions as is feasible. But even this has a limit to it. In [10], it is shown that after obtaining the maximum degree of capacity usage, even after by adding more number of radio interfaces in a network, no benefits is gained.

Figure - capacity degradation with upsurge in the number of radio interfaces per node

Figure - Effect of the number of stations and multiple radio interfaces on the throughput

In physique 14, it is shown that as long as the amount of the available channels in a cell; will be more than the number of interfaces per node, with increase in number of radios per node, throughput of the network increase [11].

Figure - throughput increment of a network by increased range of the interfaces per node

In number 15, it is shown that under a proper channel assignment and routing method, with more quantity of interfaces per node, the throughput of the machine improves noticeably [12].

In [13], as shown in number 16 and 17, performance of fixed channel allocation program is compared in detail with respect to solitary radio network and the multi-radio network.

Figure - overall network capacity increment with more volume of radio interfaces present at each node

In physique 16, it is proved that the capability of the overall system boosts with the consumption of multiple radios per node.

Figure - capacity of each AP with multiple interfaces per node - Contrast between solo radio to the multiple radios

In amount 17, per Access Point capacity is simulated to have evaluation between multi-radio software per node and sole radio user interface per node.

Dynamic Channel Allocation in Multi-radio Network:

There has been little work which demonstrates the introduction of multiple interfaces while using the Dynamic Route Allocation provides any performance up-gradation.

Analytically it is assumed that, as the benefits of multi-interfaces in cellular mesh networks increases performance, in the same way the performance of sites using Dynamic Channel Allocation can be improved upon by introducing several interface about the same node.

Some of the analysed parameters, which show the comparative improvement in performance, are listed below:

Parameter - I: Improvement in the throughput of the system:

In an individual radio cognitive network, as shown in figure 18, the node D has two data packets of equivalent size in its internal queue, one for node C and one for node. Nodes E and C are in the identical distance "d" from the node D but are tuned at different programs. In this particular case each packet will take time "t" to attain the destination. Regardless of whether we disregard the switching time, cognitive radio present at D will need to switch from one route to the other channel, the time taken to completely transmit both of the packets will be t+t = 2t.

Figure - Solitary Radio Network

Now even if the same network topology is known as but now consider that all of the nodes is equipped with two interfaces (body 19). Node D can transmit both of the packets all together to node C and node E, due to the fact interface 1 is tuned to the channel on which communication with node E can be done and program 2 is tuned to the rate of recurrence over which communication with node C is possible. In this case there will be no delay induced by the turning of the channel.

Figure - Multi-interface radio network

Figure - Effect of channel switching

Conclusion: The transmission time is reduced with the factor of "N", where N is the number of interface each one of the node will have. Throughput is better with the factor of "N".

Parameter - II: Latency of the network will lower:

With the release of the multiple interfaces in the cognitive radio network, latency of the network will reduce.

Figure - Multi-hop One interface Wifi Network

Initially taking into consideration the multi-hop situation, considering an intermediate node, it has to receive an incoming transmission on route 1 and then it must tune its radio to the channel 2 to be able transmit the received transmitting to the vacation spot node. Latency of such network will consist of:

Transmitting time of packet over channel 1 from source node to intermediate node: t1

Transmitting time of packet over route 2 from intermediate node to destination node: t2

Switching time necessary for the interface on intermediate node to switch from channel 1 to channel 2: t3

Hence the full total latency of such something will be: t1+ t2+ t3

Figure - Multi-hop Multi program Wireless Network

Now comparing the previous scenario with the main one in which each of the node is equipped with at least two interfaces. Now on the intermediate node software 1 will be tuned to channel 1 and interface 2 will be tuned to route 2. If there is an incoming transmission on channel 1 and it is to be transmitted to the channel 2, the total latency will be:

Transmitting time of packet over channel 1 from source node to intermediate node: t1

Transmitting time of packet over channel 2 from intermediate node to vacation spot node: t2

Hence the total latency of such something will be: t1+ t2

The switching time will not be considered over here; hence relatively the latency is reduced with the benefits of another program on the cognitive radio node.

Conclusion: The latency factor is dependent on turning time of the cognitive radio. This factor makes effect with an increase of dominance with upsurge in the amount of hops in the multi-hop network. Latency can be greatly reduced with the launch of multi interfaces on the cognitive radio network.

Parameter - III: Connection of the network will improve:

The probability of isolation of any node in a network will be reduced with the introduction of the multi-interfaces in the cognitive radio network.

Figure - Solo program node with the available channels

Considering the scenario, in body 23, in which a secondary network has four stations designed for its utilization, now for a given condition, all radio interfaces are tuned to either one of the route 1, 2 or 3 3. If a single interface chooses channel 4, it'll be isolated from all of those other network. Assuming that the likelihood of deciding on such a route is p then your overall probability of obtaining a node isolated from all of those other network will be p.

Figure - Multi-Interface node with the available channels

Now for multiple interfaces, a node is only going to be segregated if both the interfaces of a single node choose channel 4.

A node will be isolated if and only when:

Interface 1 chooses route 4 AND user interface 2 chooses route 4

P2

As in line with the probability rules p<=1, so p2 < p.

Conclusion: The probability of isolating a node, is lowered with the factor of "N" [N is the amount of radios] as compared to the likelihood of node isolation in case there is single program cognitive radio systems.

Here mutual self-reliance among the DCA algorithms working on both of the air interfaces is known as, but this is not generally the case. The performance of your cognitive radio network is firmly dependent on the amount of cognitive radios present in its vicinity [21].

Figure - Improvement in throughput using multiple radios

Figure - Improvement in throughput of the network with multiple radio using different number of available channels

Figure 25 and 26 shows the throughput improvement gained by the advantages of multiple radios as compared to a single radio and in both of the statistics different quantity of available channels are believed [24].

Comparison:

Up till up to now, none of the study has been carried out to determine whether any advantages is gained by deploying Active Channel Allocation plan in the multi-radio cellular network domain as compared to the implementation of the Fixed Channel Assignment algorithm. Taking into consideration the study made regarding the performance improvement gained by predetermined channel allocation scheme and dynamic route allocation structure in multi-radio cordless network, there may be several hypotheses made.

The difficulty of execution of Dynamic Channel Allocation algorithm will be more than that of Fixed Channel Allocation algorithm. Although same is true in case of solitary radio network, however in circumstance of the Multi-radio network, the complexity increment will be more significant. The reason can be studied as though the spectrum view of a single interface of your node changes in multi-radio network, for the similar node the situation changes for the other interfaces as well [21].

The performance improvement obtained by execution of the Active Route Allocation algorithm as compared to the Fixed Channel Allocation in the multi-radio will have similar results as they have in the Single radio network. Exactly the same effect on the throughput of the machine, data holding capacity and the effect of the traffic weight and traffic imbalance will be viewed.

Another essential aspect that may be predicted because of the observation made via simulation statistics is as the performance of the cellular network depends upon the density of the nodes in a network. When compared with the Fixed Channel Allocation Scheme, Active Route Allocation Algorithms could be more delicate to the density of the network [23].

There will be no matter of connectivity in the event the Fixed Channel Assignment Program is deployed on the cordless network. As prior to the point of operation with FCA, it is manufactured sure that all of the nodes are connected and none of them of the node is still left isolated. With all the Dynamic Route Allocation there will still be a small possibility that a node can get isolated from the rest of the network.

In the Fixed Route Allocation for the multi-radio cellular network the distribution of radio interfaces do not matter for the performance. But in circumstance of the DCA, better performance can be advanced if radio software distribution on the nodes is not uniform. DCA will perform better if the first hop nodes have more amount of radio interfaces than rest of the network nodes [22].

Future Work

The points brought up, during this research are just concluded through observation and analytically studying the response of the Fixed Channel Allocation Algorithm in the Multi-Radio network and Dynamic Route Allocation Algorithm in Multi-Radio Network. These observations can be further better by using proper simulating tools.

Conclusion

In the one radio cellular network, DCA exhibits better performance than FCA. The identical behaviour is expected for the multi-radio cordless network, but with the increased intricacy. And much better performance may be accomplished by taking attention of the circulation of the radios in the network. Still it ought to be considered that there will never be infinite performance gain obtained by using multi-radio network and DCA. The restriction imposed is the fact that number of stations open to a cell should always be greater than the amount of interfaces per node has.

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