Improvement at Network Planning using Heuristic Algorithm to Minimize Cost of Distance between Nodes in Wireless Mesh Networks

Wireless Mesh Networks (WMN) consists of wireless stations that are connected with each other in a semi-static configuration. Depending on the configuration of a WMN, different paths between nodes offer different levels of efficiency. One areas of research with regard to WMN is cost minimization. A Modified Binary Particle Swarm Optimization (MBPSO) approach was used to optimize cost. However, minimized cost does not guarantee network performance. This paper thus, modified the minimization function to take into consideration the distance between the different nodes so as to enable better performance while maintaining cost balance. The results were positive with the PDR showing an approximate increase of 17.83% whereas the E2E delay saw an approximate decrease of 8.33%

Performance analysis of different architectures and TCP congestion-avoidance algorithms using WMN-GA simulation system

In this paper, we evaluate the performance of two Wireless Mesh Networks (WMNs) architectures considering throughput, delay, jitter and fairness index metrics. For simulations, we used ns-3, Distributed Coordination Function (DCF) and Optimized Link State Routing (OLSR). We compare the performance of WMN for different Transmission Control Protocol (TCP): Tahoe, Reno and NewReno considering normal and uniform distributions of mesh clients by sending multiple Constant Bit Rate (CBR) flows in the network. The simulation results show that for normal and uniform distributions and both WMN architectures, the PDR values are almost the same. For Hybrid WMN, the throughput of TCP NewReno is good, but for I/B WMN, the throughput of TCP Tahoe is higher than other algorithms. For normal distribution, the delay and jitter of I/B WMN are lower compared with Hybrid WMN, while for uniform distribution, the delay and jitter of TCP NewReno are a little bit lower compared with other algorithms. The fairness index of normal distribution is higher than uniform distribution.Peer ReviewedPostprint (author's final draft

Interface and results visualization of WMN-GA simulation system: evaluation for exponential and Weibull distributions considering different transmission rates

This is a copy of the author 's final draft version of an article published in the journal Computer standards & interfaces. The final publication is available at Springer via http://dx.doi.org/10.1016/j.csi.2015.04.003In this paper, we present the interface and data visualization of a simulation system for Wireless Mesh Networks (WMNs), which is based on Genetic Algorithms (GAs). We call this system WMN-GA. As evaluation parameters, we consider Packet Delivery Ratio (PDR), throughput and delay metrics. For simulations, we used ns-3 simulator and Hybrid Wireless Mesh Protocol (HWMP). From simulation results, we found that PDR for Weibull distribution is higher than Exponential distribution. But, the throughput of Exponential distribution is higher than Weibull distribution. The delay of Exponential distribution is smaller than Weibull distribution.Peer ReviewedPostprint (author's final draft

Analysis of Mesh Router Placement in Wireless Mesh Networks Using Friedman Test

(c) 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.In this paper, we deal with connectivity and coverage problem in Wireless Mesh Networks (WMNs). We used Friedman test to compare Genetic Algorithm (GA) and Tabu Search (TS). We found out that GA and TS have difference in their performance. Then, we used the implemented systems WMN-GA and WMN-TS to evaluate and compare the performance of the system for different distributions of mesh clients in terms of giant component and covered mesh clients. The simulation results shows that for big radius of communication distances WMN-GA performs better than WMN-TS for Uniform, Normal and Weibull distributions of mesh clients. For Exponential distribution WMN-TS performs better than WMN-GA for all radius of communication distances.Peer Reviewe

Analysis of mesh router placement in wireless mesh networks using Friedman test

(c) 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.In this paper, we deal with connectivity and coverage problem in Wireless Mesh Networks (WMNs). We used Friedman test to compare Genetic Algorithm (GA) and Tabu Search (TS). We found out that GA and TS have difference in their performance. Then, we used the implemented systems WMN-GA and WMN-TS to evaluate and compare the performance of the system for different distributions of mesh clients in terms of giant component and covered mesh clients. The simulation results shows that for big radius of communication distances WMN-GA performs better than WMN-TS for Uniform, Normal and Weibull distributions of mesh clients. For Exponential distribution WMN-TS performs better than WMN-GA for all radius of communication distances.Peer Reviewe

Analysis of mesh router placement in wireless mesh networks using Friedman test considering different meta-heuristics

In this paper, we deal with connectivity and coverage problem in wireless mesh networks (WMNs). We used Friedman test to compare genetic algorithm (GA), tabu search (TS), hill climbing (HC) and simulated annealing (SA). We found out that GA, TS, HC and SA have differences in their performance. Then, we used the implemented systems WMN-GA, WMN-TS, WMN-HC and WMN-SA to evaluate and compare the performance of the systems for different distributions of mesh clients in terms of size of giant component (SGC) and number of covered mesh clients (NCMC). The simulation results show that for uniform distribution the WMN-HC and WMN-SA perform better than WMNGA and WMN-TS. However, for small radius of communication distance, the SGC of WMN-TS is better than other systems. For normal distribution, for big radius of communication distance, the WMN-GA has the best performance. For exponential distribution, the WMN-HC and WMN-SA perform better than WMN-GA for all communication distances. For Weibull distribution, the WMN-TS has a good performance for small radius of communication distance, but for big radius of communication distances the WMN-GA, WMN-HC and WMN-SA perform betterPeer Reviewe

An empirical study into, and analysis of, the impact factors of effective digital content marketing in B2B marketing in the IT industry in Singapore

The introduction of the Internet and the growth in social media platforms provide customers with vast information (Belch and Belch, 2017). However, customers no longer want to receive and consume messages that are 'controlled' by marketers (Belch and Belch, 2017). Customers want to participate by creating and contributing to the messages (Kotler et al., 2010), which gave rise to Digital Content Marketing (DCM) as a new way of communicating with customers (Solomon, 2013; Rao et al., 2014). DCM that takes a publishing approach to provide targeted content (Holliman and Rowley, 2014) and a storytelling approach to establish the brand's emotional connection (Kee and Yazdanifard, 2015) could attract the audience more effectively than traditional marketing (Pulizzi, 2015). Therefore, DCM was said to be the future of marketing communications (Gábor, 2016). DCM is more widely adopted by marketers in business-to-business (B2B) selling than business-to-consumer (B2C) selling (Järvinen and Taiminen, 2016), and 70% of them planned to produce more content for lead generation as the top objective (Pulizzi and Handley, 2017a). Therefore, it is important to understand the impact factors of DCM that could effectively generate sales leads, especially when B2B marketers are measured on leads generation. Yet, academic research on DCM in B2B marketing is very limited (Taiminen and Ranaweera, 2019). This study identifies the impact factors of DCM for effective sales leads generation in Singapore's B2B marketing in the Information Technology (IT) industry. From the literature review, gap analysis and literature synthesis of existing research and literature on this topic, four impact factors were identified, which formed the propositions for this study. The four impact factors are emotionality in content, company-owned content, referred content and job role. The integrative methodology (Wright, 2011) aligned to the pragmatic research paradigm (Johnson and Onwuegbuzie, 2004) was used in this study that combined both the quantitative and qualitative methods, otherwise known as mixed methods (Firestone, 1987, Creswell, 2009). Digital content that displayed the impact factors being evaluated were created for the testing in a phenomenological research design. Using the Sequential Explanatory Design approach to mixed methods, data were collected using an online questionnaire from subjects to determine the extent to which the content would interest them to find out more about the brand or product. After that, a semi structured interview was conducted to provide additional insights. The sample comprises 203 Singapore-based IT decision-makers and influencers who leverage DCM in the buying cycle of IT products for their organisations. This study concludes that emotionality in content is more impactful in generating leads among B2B customers than factual content. Marketing practitioners should leverage storytelling to evoke emotions and interest in the products among customers, especially at the early stage of their buying cycle when they have yet shortlisted brands or products for consideration. However, it is not conclusive whether company-owned content is more impactful than referred content and vice versa. Customers would leverage company-owned content when they have identified or shortlisted a few brands or products for comparison and evaluation. On the other hand, referred content is regarded as useful when selecting products for consideration and making the final decision. This study also concludes that the impact of DCM and the impact factors varied by job roles. Customers in non-IT related roles are more likely to turn to DCM for information. Content that evokes emotions is impactful across all the job roles except for IT leadership and developer roles. Company-owned content is preferred by customers in IT-related roles, while referred content would impact customers across all job roles, especially non-IT related roles. There is a significant difference in the impact of DCM and the impact factors between IT managers and customers in non-IT related roles. The conclusions provide practical frameworks, recommendations and guidance to B2B marketing practitioners on how to apply the impact factors to increase the Return on Investment (ROI) of marketing spend on DCM. While this study is conducted in Singapore due to the availability of subjects and its value to many IT companies headquartered in Singapore, the findings may also be applied to the other Asia Pacific and Western countries