Performance Analysis for AD-HEED and N-HEED

Per prep arance summary for AD- direction and N- heed4.1 Results and DiscussionIn this section, we exhibit and treat the upshots of the simulation. This section luffs the performance analysis for AD- worry and N- bear in mind compargond to the original HEED communications protocol. Every result presented is the average of five experiments. The following sections give a detailed verbal description of the experiments and the results.4.4.1 Net convey LifetimeThe estimate of alive knobs for distributively round is spy for AD-HEED and N-HEED comp ard to HEED protocol to evaluate the life story of the internet. In the proposed methods and according to the blank mingled with the CH and its backbone, we proposed AD-HEED30, AD-HEED87, N-HEED30 and N-HEED87. 30 and 87 are the exceed among the CH and its anchor (dch_to_Anc) where 30 is the cluster radius and 87 is the doorsill aloofness which depends on the environment. According to simulation results, AD-HEED87 and N-HEED87 h ave the same results for only(prenominal) experiments so N-HEED87 results leave non be appeared in any chassis.In all of the experiments, the sensing element nodes were deployed uniformly. run across 41 shows the performance of HEED protocol compared to AD-HEED and N-HEED. It is observe that AD-HEED87 outperforms HEED and the other proposed methods. AD-HEED87 increases the net income lifespan until all nodes pass their substantial talent by much than 150 rounds compared with HEED protocol. N-HEED30 too increases the communicate life story by more than 50 rounds until the whole nodes die. meet 41 Number of alive nodes per rounds realise 42 presents how AD-HEED and N-HEED yield with HEED protocol in shape of node shoemakers last ploughshare. The figure downstairs shows the act of rounds for 10%, 25%, 50%, 75% and 90% of nodes that consume their whole brawniness. The results show that AD-HEED and N-HEED outperform HEED throughout the interlock. on that point i s a slight advantage to HEED on AD-HEED30 in 90% of nodes oddment .The figure shows that for 10% of nodes death, the silk hat choice is AD-HEED30 and N-HEED30 musical composition the shell choice for 75% and 90% of nodes death is AD-HEED87. For 25% and 50% of nodes death the best choice occurs with all proposed methods because they are rough the same. According to both(prenominal) of figures, the results show that our proposed methods outperform HEED. throw 42 Node death percentage per rounds4.4.2 Energy Consumption AnalysisThe performance of AD-HEED and N-HEED is compared with that of HEED protocol in border of ability economic utilization for entropy contagion amidst CHs and the bow rate. icon 43 reveals the ratio of strength inspiration for AD-HEED and N-HEED per rounds compared with HEED. Here, the efficacy consumption is the brawniness consumed by nodes to get entropy to the immoral brand. According to the listed parameters, the results show that the pus h button consumption for entropy contagion between CHs and the theme change is approximately 19% from the whole naught in HEED protocol. According to our experiments, we have a network that consists of 200 sensors deployed in 100m 100m, the shank localise regain away at (200, 200) from the surrounding subject and the initial vigour for each node is 2 J. The total dynamism for 200 nodes is 400 J and then the life force consumed to propagate info from CHs to the radical station is 76 J (19% of 400 J). The figure beneath shows that AD-HEED87 is the lowest energy consuming and then N-HEED30 and AD-HEED30 respectively which room that all of them consumed energy lower than that consumed by HEED. AD-HEED87 decreases the energy consumption by HEED by al almost 47% and this means it consumes 36 J for information transmission. look-alike 43 The ratio of energy consumption per rounds cast 44 presents the ratio of energy consumption in data transmission in term of node death percentage. The figure below shows the ratio of energy consumption for 10%, 25%, 50%, 75% and 90% of nodes that consume their whole energy. As it is obviously clear from the figure, AD-HEED and N-HEED consume lower energy than HEED throughout the network. AD-HEED87, N-HEED30 and AD-HEED30 are the lowest energy consumption respectively. physical body 44 The ratio of energy consumption for AD-HEED, N-HEED and HEEDTable 42 reveals the melioration of energy consumed for data transmission of AD-HEED and N-HEED on HEED protocol for 10%, 25%, 50%, 75% and 90% of nodes death. The comparison results shown in Table 42 depict that AD-HEED87, N-HEED and AD-HEED30 respectively are more energy efficient than HEED throughout the network. It is worth mentioning here that the data transmission energy is the energy consumed to air out data from CHs to the idea station.Table 42 melioration of AD-HEED and N-HEED on HEED protocol4.4.3 Variance of the Base Station spatial relationIn this set o f experiments we evaluate how varying the location of the foundation garment station could effect on both schemes AD-HEED and N-HEED in term of network animation and energy consumption. throw 45 compares the lifetime of the network of AD-HEED and N-HEED with HEED, where the network lifetime is the time until the first 10% of nodes die and when the locations of the show station are (150, 150), (200, 200) and (250, 250) on x-coordinate and y-coordinate. Similar comparisons are conducted for the network lifetime in term of HND and LNA10% as exhibited in Figure 46 and Figure 47 respectively. Both preludees improve the network lifetime with contrary locations for the household station compared to HEED protocol. Figure 45 shows that AD-HEED30 is the best choice where the network lifetime is FND10%.Figure 45 examine HEED with AD-HEED and N-HEED exploitation dia metric functional locations of the petty(a) station for FND10% metricFigure 46 and Figure 47 show that AD-HEED87 and N- HEED30 follow network lifetime in term of HND and LNA10% while AD-HEED30 prolongs network lifetime in term of HND and LNA10% while AD-HEED30 prolongs network lifetime in term of HND. Thus, for the occupation that requires that at least 90% of nodes should work, AD-HEED30 is the best choice and suspend for improving the network lifetime in term of FND10%. If the demand of the application is to boost the lifespan of the network in term of LNA10%, then AD-HEED87 entrust be appropriate because they improve the network lifetime in term of LNA10% significantly.Figure 46 compare HEED with AD-HEED and N-HEED victimisation diametrical locations of the rear station for HND metricIt can be easily ascertained form Figure 45, Figure 46 and Figure 47 that if the base station location is farther, the network lifetime will decrease in term of FND10%, HND and LNA10% in AD-HEED and N-HEED. The decreasing of network lifetime is due to consuming more energy to transmit data to the base station. We know that the anchor or CH consumes (k (Eelec + Eamp * dn)) J to transmit k-bit contentedness to the base station where n = 2 for d 0, and n = 4 for d d0. Thus, the outstrip between the immediate node and the base station according to the experiments is greater than 87 (d0) so n = 4 all the time. In other words, whenever the base station was nearer, CHs and anchors will consume slight energy to deliver data to the base station and vice versa. This means that the surmount between CHs or anchors and the base station is a detailed factor which effects on the energy consumption.Figure 47 Comparing HEED with AD-HEED and N-HEED employ contrastive locations of the base station for LNA10% metricThe following trey figures present the energy consumed in Joules by HEED, AD-HEED and N-HEED using different locations of the base station. From the figures, it is clear that AD-HEED and N-HEED consume less energy than HEED protocol throughout the network. The energy saving by the prop osed method increases as the location of the base station was farther. The explanation of this was aforementioned. It is clear from the figures that the member of improvement decreases as we go through the network lifetime. In other words, the fraction of improvement in the energy consumption for FND10% is greater than that for HND and LNA10%. This is due to that in the earlier periods of the network lifetime there are a attraction of nodes that not consume their whole energy. Thus, CHs can select the beast node as anchor which is the closest node to the base station. But in the in the later periods of the network lifetime, a lot of nodes die. Thus, some of CHs may not use anchor to transmit data the base station or select a node as anchor which not effect on energy consumption impressively. Figure 48, Figure 49 and Figure 410 reveal that AD-HEED87 is the most energy saving and then N-HEED30 and AD-HEED30.Figure 48 The energy consumption using different locations of the base stat ion for FND10% metricFigure 49 The energy consumption using different locations of the base station for HNDFigure 410 The energy consumption using different locations of the base station for LNA10% metric4.4.4 Variance of the Number of SensorsWe overly evaluate the effectiveness of increasing subdue of the nodes on both methods AD-HEED and N-HEED. Figure 411 compares the lifetime of the network of HEED to AD-HEED and N-HEED, where the network lifetime is FND10% and when the number of nodes is varied between 150, 200, 250 and 300 nodes. Identical comparisons are conducted for HND and LNA10% as depicted in Figure 412 and Figure 413 respectively. Both methods improve the network lifetime as the number of nodes increases. The figures show that, in almost all cases, AD-HEED and N-HEED performs better than HEED. This improvement is also due to using the anchor as intermediate between CHs and the base station. This increases the network lifespan and decreases the energy consumption. The figures show that AD-HEED30 outperforms the others in term of FND10% while AD-HEED87 outperforms the other in term of LNA10% as the number of sensors increases. AD-HEED87 and N-HEED30 are approximately the same with a slight advantage to AD-HEED87 in term of HND.Figure 411 Comparing HEED with AD-HEED and N-HEED using different number of sensors for FND10% metricFigure 412 Comparing HEED with AD-HEED and N-HEED using different number of sensors for HND metricFigure 413 Comparing HEED with AD-HEED and N-HEED using different number of sensors for LNA10% metricThe following three figures present the energy consumed in Joules by HEED, AD-HEED and N-HEED using different number of sensors.Figure 414 The energy consumption using different number of sensors for FND10% metricIt is obviously clear that AD-HEED and N-HEED are more energy efficient because they consume less energy than HEED protocol in all experiments throughout the network. It can be easily observed form the figures that the pe rcentage of improvement is almost the same when the number of the nodes increases. So, the proposed methods doesnt call for by varying the number of sensors.Figure 415 The energy consumption using different number of sensors for HND metricFigure 416 The energy consumption using different number of sensors for LNA10%4.4.5 Results AnalysisIn HEED protocol, each sensor gathers data and forwards it to its CH. CHs in turn aggregate data from sensors and transmit it to the base station which fit(p) far away from the surrounding area. CHs consume their energy during data accrual from sensors, data compression per place and forwarding them to the base station.Where ET is energy consumed for transmission of K bits for distance d, ER is energy consumed for receiving, Eelec is energy consumed by the sensor node circuit, Eamp is the energy consumed by amplifier and Efus is the energy consumed for data fusion.Our proposed technique focuses on data transmission between CHs and the base statio n. The energy consumed by CH to transmit data to the base station directly (EnDir) represents a certain percentage of the whole energy. This percentage differs according to many factors such(prenominal) as the base station location, number of sensors and etc. the energy consumed for direct data transmission is expectd as the followingEnDir = EnCH_to_BSEnCH_to_BS = The energy consumed to transmit data to the base station indirectly via anchor (EnIndir) is calculated as the followingEnIndir = EnCH_to_Anc + EnAnc_to_BSEnCH_to_Anc = (1)EnAnc_to_BS = + (2)Where n =2 if d 0 or n = 4 if d d0. The energy of (1) is consumed for transmission data to the anchor by CH while the energy of (2) is consumed for receiving data from CH and forwarding it to the base station by anchor.In AD-HEED, CHs transmit the collected data to their anchors if EnDir EnIndir and anchors in turn transmit data to the base station. other than CHs transmit the gathered data to the base station directly.In N-HEED and in addition to AD-HEED, the current anchors transmit the gathered data to the bordering anchors if EnDir EnIndir and the next anchors in turn transmit data to the base station. Otherwise the current anchors transmit the gathered data to the base station directly.Figure 417shows the detailed description of how can transmitting data via anchors conquer the energy consumption. If we assume that the point a is the CH, d is the base station and b, c and e are hypothetical points that located in the CHs transmission range which represented by a circle. The deployment field is 100m x 100m and the base station located away at (200, 200) m from the network field. The transmission range is 30 (cluster radius). ac = ab = 30. ad is the distance between CH and the base station while bd, cd and ed are the distances between the points b, c and e respectively and the base station. According to our proposed technique, CH selects the closest sensor to the base station to be its anchor and it shou ld be enveloping(prenominal) than CH itself. Firstly, we assume that the distance between the base station (d) and point (c) is personify to the distance between the base station and CH (a). afterward that, we reduce the distance cd by moving the position of point c and calculate the energy consumed to transmit one byte from CH (a) to the base station directly (EnDir) and the energy consumed to transmit one byte from CH to the base station indirectly (EnIndir) via point (c). This deed repeats many times until EnDir EnIndir. The same operations are conducted with point (b). After testing and calculation and by assuming that c, b and e are sensors, we get that cd and bd are the maximum distances while ed is the stripped distance in which sending data to the base station indirectly via sensors c, b or e consumes less energy than sending data directly from CH to the base station. Now, we can see that for any sensor located in the gray zone in the circle and has a distance to the b ase station less than the maximum distance, transmitting data from CH to the base station via any of these sensors will consume less energy than energy consumed by transmitting data from CH directly to the base station.Figure 417 The mechanism of sending data via anchorsChapter Two Conclusions and Future work5.1 ConclusionsIn this research, we proposed an efficient mechanism for hierarchal protocols of radio set sensor networks which turn out to be more efficient in the use of energy than HEED protocol in most cases. The main contribution is to allow CHs to transmit data by using other sensors called anchors as intermediates which are hand-to-hand to the base station than CHs. Furthermore, this approach reduces the burden from the CHs which consume their energy by collecting data from sensors and forwarding them to the base station. The sensor which has the collected data compares between the energy consumed in case if it transmits data directly to the base station and if it tran smits data indirectly to the base station via its anchor. After that, the sensor decided either to transmit data directly or via anchors to the base station base on way that consumes less energy. We compared and evaluated the proposed approach performance with the HEED protocol in terms of network lifetime and energy consumption. Simulation results depict that the proposed methods which called AD-HEED and N-HEED perform better than HEED. The improvement percentage relies on the best choice of the distance between the CH and the anchor, the evaluation metrics and the properties of the wireless sensor network. This improvement is because of that the sensor consumes much less energy when they transmit data to sensor closer than another. We know that the CH consumes (k (Eelec + Eamp * dn)) J to transmit k-bit pass along to the base station. If the distance between CH and the base station less than threshold distance, the energy consumption equation is calculated by using distance to th e power of 2 otherwise, to the power of 4. So, the energy consumption is decreased by using anchorswhich allow sensors to transmit data via short distances until all data received by the base station. According to simulation results, the distance between CH and the base station is very critical factor which effects on the network lifetime and energy consumption .Furthermore we also conduct a performance evaluation between our proposed approach and HEED protocol by using different number of sensors and different locations of the base station. The simulation results show that the variation in the number of sensors doesnt affect significantly on the percentage of improvement. The simulation results show also that the percentage of improvement decreases as the location of the base station was farther because the sensors consume more energy whenever transmitting data over long distances.5.2 Future Workthough considerable effort has been made on this thesis, many ideas regarding the subje ct are still not investigated. This section outlines and presents some of our future plans to be conducted in order to improve this work.The choosing of anchors in our approach depended entirely on the distance between the sensors and the base station where CHs choose the closest sensor to the base station. We think to make the choosing of anchors more controlled by taking into account different conditions and other related parameters such as the residual energy, the positions of the nodes and the received signal strength.The collected data by sensors is transmitted by CHs to one base station. This assumption is similar to that in HEED protocol. For scenarios where there are more than one base station located in different locations, each CH should transmit data to the suitable base station. Thus, studying how our proposed approach behaves with these scenarios is a very good idea to be conducted for future work.Finally, the energy consumption and network lifetime are the only perform ance metrics that are used to evaluate our proposed approach. Using other performance metrics such as throughput, latency and packet delivery ratio to evaluate the proposed approach is a good idea to be conducted for future work.