Effective Capacity Modulation as an Explicit Control Knob for Public Cloud Profitability

2018 ◽  
Vol 13 (1) ◽  
pp. 1-25 ◽  
Author(s):  
Cheng Wang ◽  
Bhuvan Urgaonkar ◽  
George Kesidis ◽  
Aayush Gupta ◽  
Lydia Y. Chen ◽  
...  
Author(s):  
M. Chaitanya ◽  
K. Durga Charan

Load balancing makes cloud computing greater knowledgeable and could increase client pleasure. At reward cloud computing is among the all most systems which offer garage of expertise in very lowers charge and available all the time over the net. However, it has extra vital hassle like security, load administration and fault tolerance. Load balancing inside the cloud computing surroundings has a large impact at the presentation. The set of regulations relates the sport idea to the load balancing manner to amplify the abilties in the public cloud environment. This textual content pronounces an extended load balance mannequin for the majority cloud concentrated on the cloud segregating proposal with a swap mechanism to select specific strategies for great occasions.


2018 ◽  
Vol 31 (5-6) ◽  
pp. 227-233
Author(s):  
Weitao Wang ◽  
◽  
Baoshan Wang ◽  
Xiufen Zheng ◽  

2018 ◽  
Vol 31 (1) ◽  
pp. 244
Author(s):  
Nada M. Al-Hakkak ◽  
Ban Salman Shukur ◽  
Atheel Sabih Shaker

   The concept of implementing e-government systems is growing widely all around the world and becoming an interest to all governments. However, governments are still seeking for effective ways to implement e-government systems properly and successfully. As services of e-government increased and citizens’ demands expand, the e-government systems become more costly to satisfy the growing needs. The cloud computing is a technique that has been discussed lately as a solution to overcome some problems that an e-government implementation or expansion is going through. This paper is a proposal of a  new model for e-government on basis of cloud computing. E-Government Public Cloud Model EGPCM, for e-government is related to public cloud computing.


2021 ◽  
pp. 204388692098158
Author(s):  
Dipankar Chakrabarti ◽  
Rohit Kumar ◽  
Soumya Sarkar ◽  
Arindam Mukherjee

Industrial Internet of Things emerged as one of the major technologies enabling Industry 4.0 for industries. Multiple start-ups started working in the Industrial Internet of Things field to support this new industrial revolution. Distronix, one such Industrial Internet of Things start-up of India, started operations in 2014, when companies were not even aware of Industrial Internet of Things. Distronix started executing fixed-fee projects for implementation of Industrial Internet of Things. They also started manufacturing sensors to support large customers end-to-end in their Industry 4.0 journey. With the advent of public cloud, companies started demanding pay-per-use model for the solution Distronix provided. This posed a major challenge to Distronix as they had developed technology skills focusing fixed-fee customized project delivery for their clients. The situation demanded that they change their business model from individual project delivery to creation of product sand-box with pre-registered sensors and pre-defined visualization layer to support use cases for Industrial Internet of Things implementation in multiple industry sectors. It forced Rohit Sarkar, the 26 years old entrepreneur and owner of Distronix, to upgrade capabilities of his employees and transform the business model to support pay-per-use economy popularized by public cloud providers. The case discusses the challenges Rohit faced to revamp their business model in such an emerging technology field, like, to develop new skills of the technical people to support such novel initiative, reorienting sales people towards pay as use model, developing new concept of plug and play modular product, devising innovative pricing, better alliance strategy and finding out a super early adopter.


Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1493
Author(s):  
Ayesha Ayub ◽  
Sobia Jangsher ◽  
M. Majid Butt ◽  
Abdur Rahman Maud ◽  
Farrukh A. Bhatti

Small cells deliver cost-effective capacity and coverage enhancement in a cellular network. In this work, we present the interplay of two technologies, namely Wi-Fi offloading and small-cell cooperation that help in achieving this goal. Both these technologies are also being considered for 5G and B5G (Beyond 5G). We simultaneously consider Wi-Fi offloading and small-cell cooperation to maximize average user throughput in the small-cell network. We propose two heuristic methods, namely Sequential Cooperative Rate Enhancement (SCRE) and Sequential Offloading Rate Enhancement (SORE) to demonstrate cooperation and Wi-Fi offloading, respectively. SCRE is based on cooperative communication in which a user data rate requirement is satisfied through association with multiple small-cell base stations (SBSs). However, SORE is based on Wi-Fi offloading, in which users are offloaded to the nearest Wi-Fi Access Point and use its leftover capacity when they are unable to satisfy their rate constraint from a single SBS. Moreover, we propose an algorithm to switch between the two schemes (cooperation and Wi-Fi offloading) to ensure maximum average user throughput in the network. This is called the Switching between Cooperation and Offloading (SCO) algorithm and it switches depending upon the network conditions. We analyze these algorithms under varying requirements of rate threshold, number of resource blocks and user density in the network. The results indicate that SCRE is more beneficial for a sparse network where it also delivers relatively higher average data rates to cell-edge users. On the other hand, SORE is more advantageous in a dense network provided sufficient leftover Wi-Fi capacity is available and more users are present in the Wi-Fi coverage area.


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