The Role of Responsive Pricing in the Internet

The Internet continues to evolve as it reaches out to a wider user population. The recent introduction of user-friendly navigation and retrieval tools for the World Wide Web has triggered an unprecedented level of interest in the Internet among the media and the general public, as well as in the technical community. It seems inevitable that some changes or additions are needed in the control mechanisms used to allocate usage of Internet resources. In this paper, we argue that a feedback signal in the form of a variable price for network service is a workable tool to aid network operators in controlling Internet traffic. We suggest that these prices should vary dynamically based on the current utilization of network resources. We show how this responsive pricing puts control of network service back where it belongs: with the users.Internet, pricing, feedback, networks

A Review on Energy Consumption Optimization Techniques in IoT Based Smart Building Environments

In recent years, due to the unnecessary wastage of electrical energy in residential buildings, the requirement of energy optimization and user comfort has gained vital importance. In the literature, various techniques have been proposed addressing the energy optimization problem. The goal of each technique was to maintain a balance between user comfort and energy requirements such that the user can achieve the desired comfort level with the minimum amount of energy consumption. Researchers have addressed the issue with the help of different optimization algorithms and variations in the parameters to reduce energy consumption. To the best of our knowledge, this problem is not solved yet due to its challenging nature. The gap in the literature is due to the advancements in the technology and drawbacks of the optimization algorithms and the introduction of different new optimization algorithms. Further, many newly proposed optimization algorithms which have produced better accuracy on the benchmark instances but have not been applied yet for the optimization of energy consumption in smart homes. In this paper, we have carried out a detailed literature review of the techniques used for the optimization of energy consumption and scheduling in smart homes. The detailed discussion has been carried out on different factors contributing towards thermal comfort, visual comfort, and air quality comfort. We have also reviewed the fog and edge computing techniques used in smart homes

Improving perceptual multimedia quality with an adaptable communication protocol

Copyrights @ 2005 University Computing Centre ZagrebInnovations and developments in networking technology have been driven by technical considerations with little analysis of the benefit to the user. In this paper we argue that network parameters that define the network Quality of Service (QoS) must be driven by user-centric parameters such as user expectations and requirements for multimedia transmitted over a network. To this end a mechanism for mapping user-oriented parameters to network QoS parameters is outlined. The paper surveys existing methods for mapping user requirements to the network. An adaptable communication system is implemented to validate the mapping. The architecture adapts to varying network conditions caused by congestion so as to maintain user expectations and requirements. The paper also surveys research in the area of adaptable communications architectures and protocols. Our results show that such a user-biased approach to networking does bring tangible benefits to the user

Adaptive and Resilient Revenue Maximizing Dynamic Resource Allocation and Pricing for Cloud-Enabled IoT Systems

Cloud computing is becoming an essential component of modern computer and communication systems. The available resources at the cloud such as computing nodes, storage, databases, etc. are often packaged in the form of virtual machines (VMs) to be used by remotely located client applications for computational tasks. However, the cloud has a limited number of VMs available, which have to be efficiently utilized to generate higher productivity and subsequently generate maximum revenue. Client applications generate requests with computational tasks at random times with random complexity to be processed by the cloud. The cloud service provider (CSP) has to decide whether to allocate a VM to a task at hand or to wait for a higher complexity task in the future. We propose a threshold-based mechanism to optimally decide the allocation and pricing of VMs to sequentially arriving requests in order to maximize the revenue of the CSP over a finite time horizon. Moreover, we develop an adaptive and resilient framework based that can counter the effect of realtime changes in the number of available VMs at the cloud server, the frequency and nature of arriving tasks on the revenue of the CSP.Comment: American Control Conference (ACC 2018