Husnu S. Narman

Scheduling internet of things applications in cloud computing

Internet of Things (IoT) is one of the greatest technology revolutions in the history. Due to IoT potential, daily objects will be consciously worked in harmony with optimized performances. However, today, technology is not ready to fully bring its power to our daily life because of huge data analysis requirements in instant time. On the other hand, the powerful data management of cloud computing gives IoT an opportunity to make the revolution in our life. However, the traditional cloud computing server schedulers are not ready to provide services to IoT because IoT consists of a number of heterogeneous devices and applications which are far away from standardization. Therefore, to meet the expectations of users, the traditional cloud computing server schedulers should be improved to efficiently schedule and allocate IoT requests. There are several proposed scheduling algorithms for cloud computing in the literature. However, these scheduling algorithms are limited because of considering neither heterogeneous servers nor dynamic scheduling approach for different priority requests. Our objective is to propose dynamic dedicated server scheduling for heterogeneous and homogeneous systems to efficiently provide desired services by considering priorities of requests. Results show that the proposed scheduling algorithm improves throughput up to 40 % in heterogeneous and homogeneous cloud computing systems for IoT requests. Our proposed scheduling algorithm and related analysis will help cloud service providers build efficient server schedulers which are adaptable to homogeneous and heterogeneous environments by considering system performance metrics, such as drop rate, throughput, and utilization in IoT.

Multi class traffic analysis of single and multi-band queuing system

To facilitate higher bandwidth for multimedia traffic, modern routers support simultaneous multi-band communication, leading to less interference, higher capacity and better reliability. However, there is lack of quantitative evaluation to judge whether multi-band is better than single band router in realistic scenarios. Our objective is to propose a scheduling algorithm for multi-band routers and compare single band and multi-band system with different allocation policies. We have used different scheduling algorithms for multi-band routers which transmit different classes of traffic through different frequency bands, thereby achieving improved performance. By comparing multi-band and single band mobile router performances, we have found out that one of them is not always better than the other although multi-band is expected to have better performance.

DDSS: Dynamic dedicated servers scheduling for multi priority level classes in cloud computing

Simplicity of usage, flexibility of data access, ease of maintenance, time and energy efficiency, and pay as you go policy have increased the usage of cloud computing over traditional computing. Cloud computing should be able to meet the performance expectations of different classes of customers. On the contrary, inefficient scheduling algorithms decrease the quality of service experienced by users. To improve quality of service, there are several proposed scheduling algorithms in the literature. However, these scheduling algorithms are limited because they do not consider different types of customers. Our objective is to satisfy performance expectations of customers by proposing an efficient Dynamic Dedicated Server Scheduling (DDSS) while considering different types of customers. Results show that the customer drop rate and throughput can be significantly improved by DDSS. Our proposed scheduling and related analysis will help cloud service providers build efficient cloud computing service architectures through considering different types of priority class performances such as, drop rate, throughput, and utilization.

A novel scheduling and queue management scheme for multi-band mobile routers

Recent trends in Internet usage have seen large amount of multimedia data due to increasingly large number of mobile users. To facilitate higher bandwidth, modern mobile routers are capable of supporting simultaneous multi-band, leading to less interference, higher capacity. However, there exists no previous work that attempts to maximize utilization through sharing of traffic among different frequency bands. In this paper, we have proposed a novel scheduling algorithm for multi-band mobile routers which transmits different classes of traffic through different frequency bands to achieve improved performance. We have developed an analytical model to perform queuing analysis of the proposed multi-band system and derived various performance metrics, validated by extensive simulations. Our results show that the proposed architecture can ensure maximum possible utilization through sharing of capacities among the bands. Our proposed scheduling algorithm and related analytical model can help network engineers build next generation mobile routers with higher throughput and utilization ensuring least packet loss for different classes of traffic.

Management and Analysis of Multi Class Traffic in Single and Multi-band Systems

A recent trend in Internet usage has seen large amounts of multimedia data due to increasingly large numbers of mobile users. To facilitate higher bandwidth, modern mobile routers are capable of supporting simultaneous multi-band, leading to less interference, higher capacity and better reliability. However, there exists neither previous work that attempts to maximize utilization of available bandwidth in order to increase performance of multi-band mobile routers through the sharing of traffic classes among different frequency bands of the multi-band mobile router by scheduling, nor that shows multi-band routers are better than single band routers in realistic scenarios. In this paper, we have proposed a novel scheduling algorithm for multi-band mobile routers which transmits different classes of traffic through different frequency bands to achieve improved performance. We have developed an analytical model to perform queuing analysis of the proposed scheduling algorithm for multi-band mobile routers and derived various performance metrics, validated by extensive simulations. Our results show that the proposed scheduling model can improve performance by ensuring maximum possible utilization through sharing of capacities among the bands in multi-band systems. We show our results by comparing proposed multi-band scheduling model with single and current multi-band scheduling models. In addition, we compare single and multi-band mobile routers. It is evident from our results that multi-band systems are not always better than single band systems although multi-band systems are expected to have better performance. Based on the results, we have listed recommendations for selecting single or multi-band systems and allocation policies according to traffic conditions, and their priorities. Our proposed scheduling algorithms and related analysis will help network engineers build next generation mobile routers with higher throughput and utilization, ensuring less packet loss of different classes of traffic.

h-DDSS: Heterogeneous Dynamic Dedicated servers scheduling in cloud computing

Simplicity of usage, flexibility of data access, ease of maintenance, time and energy efficiency, and pay as you go policy have increased the usage of cloud computing over traditional computing. Cloud computing should be able to meet the performance expectations of different classes of customers. However, inefficient scheduling algorithms decrease the quality of service experienced by users. To improve quality of service, several scheduling algorithms have been proposed in the literature. However, these scheduling algorithms do not consider heterogeneous servers or different priority classes of customers. Our objective is to satisfy performance expectations of customers by proposing a Heterogeneous Dynamic Dedicated Server Scheduling (h-DDSS) while considering heterogeneous servers and different priority classes of customers. Results show that h-DDSS architecture can provide improved customer throughput and drop rate over homogeneous DDSS in cloud computing. Our proposed scheduling algorithm and related analysis will help cloud service providers build efficient cloud service architectures which are adaptable to homogeneous and heterogeneous environments by considering different types of priority class performances, such as, drop rate, throughput, and utilization.

Utilizing distance distribution in determining topological characteristics of multi-hop wireless networks

Understanding the topological characteristics of communications networks is essential to the design and operation of such networks. Accordingly, the researchers have been analyzing the topological characteristics of various networks. In this paper, we focus on multi-hop wireless networks with uniformly distributed nodes in 2D and 3D environments. Using the geometrical relations in 2D, researchers have provided analytical formulas for some topological characteristics. However, generalizing this approach to 3D is difficult as it requires to carefully analyze several geometrical relations that overlap. Instead, we consider the distance distribution between two random points, which has been extensively studied in both 2D and 3D. Using these important results, we derive analytical formulas for various topological characteristics in both 2D and 3D. Using simulations, we verify the correctness of our analytical formulas.

Joint and selective periodic component carrier assignment for LTE-A

The bandwidth demand for mobile Internet access is significantly increased with the number of mobile users. Carrier aggregation has been proposed to answer this demand in mobile networks. In carrier aggregation, the best available one or more component carriers of each band are assigned to each user to provide efficient services. Several works have been reported in the literature on mandatory and periodic component carrier assignment methods. Although the former works, especially periodic component carrier assignment methods, have significantly improved the performance of LTE-A systems, many limitations still exist. One limitation of previous works is that data transfer is interrupted during periodic component carrier assignment operations thus, decrease the performance of the system. Therefore, in this paper, selective periodic component carrier assignment technique, which allows continuous data transfer during periodic carrier assignment operations, is proposed and followed by integration of selective technique into four component carrier assignment methods: Least Load, Least Load Rate, Random, and Channel Quality to observe the performance improvements. Results indicate that the proposed selective technique increases the throughput ratio up to 18% and decreases average delay up to 50%. Our analysis and proposed technique will assist service providers to build efficient periodic component carrier assignment methods to improve the performance of the system by reducing delay and increasing throughput ratio.