Vishal Garg

Smartphone devices have occupied an indispensable place in human life. These devices
have some restrictions, like short lifetime of battery, imperfect computation power,
less memory size and unpredictable network connectivity. Hence, a number of methods
previously presented to decrease these restrictions as well as increase the battery
lifespan with the help of offloading strategy. This manuscript proposes anewenhancing
mobile data security using red panda optimized approach with chaotic fuzzy encryption
in mobile cloud computing (RPO-CFE-SMC) to offload intensive computation
tasks from mobile device to the cloud. The proposed model utilizes a red panda optimization
algorithm (RPOA) to scale dynamically the offloading decision under energy
consumption, CPU utilization, execution time, memory usage parameters. Before the
work is transferred to the cloud, an innovative security layer is applied for encrypting
the data using AES chaotic fuzzy encryption (CFE) technology. The proposed
RPO-CFE-SMC method provides 20.63%, 25.25%, 25.28%, and 32.47% lower encryption
time and 23.66%, 24.25%, and 26.47% lower energy consumption compared with
existing EFFORT-SMC, EESH-SMC, and CP-ABE-SMC models respectively. In conclusion,
the simulation results prove that the improved efficiency of proposed model in
offloading computation to the cloud with enhanced data protection using chaotic fuzzy
encryption.

This paper uses the chaotic fuzzy encryption (CFE) technique and a greedy chemical reaction
optimization algorithm based on mobile cloud computing to protect data from any assault.
Mobile users who use protected mobile cloud computing (Mobi-Cloud) must trust the cloud
service provider to keep the data sent from their mobile devices safe when mobile users express
strong reservations about storing personal information in the public cloud. The Greedy Chemical
Reaction Optimization (G-CRO) algorithm reduces critical limitations by determining the
offloading end with motion at run time, i.e., the task's operating time, CPU usage, memory
utilization, and energy usage. The experimental results show that the proposed method performs
better in terms of file uploading time, file downloading time, memory usage in file uploading,

This paper explains the project’s objectives, identifies the key stakeholders, defines the
project manager’s authority and provides a preliminary breakdown of roles and responsibilities. For
the project’s future, it acts as a source of authority. This paper’s objective is to record the justifications
for starting the project, its goals, limitations, solution instructions and the names of the principal
stakeholders. This manuscript is meant to be used as a “Project Management Plan Light” for small and
medium-sized projects when it would be uneconomical to prepare an entire collection of documents
that make up a project management plan. A global media cloud will be provided and managed by
the ABC cloud company inside of a consumer’s current premises. In this paper, the authors explain
the end-to-end delivery of cloud and compute services. The article mainly focuses on the delivery
of virtual machines (VMs), graphics processing unit (GPUs), cloud storage, transcoding, packaging,
24/7 customer support and billing modules for the services used by end customers. The process
starts with customer requirements gathering to initiate the feasibility check for the services desired
or required by the clients. Pre-sale solution engineers capture all the customer requirements in the
solution design document to review with the engineering and delivery team for the implementation.
Based on the solution design document, the solution engineer needs to raise the system’s feasibility
for the local loops, cross connects, VMs, GPUs, storage, transcoders and packagers required to meet
the end customer expectations on the service delivery. The solution engineer must sign-off on the
solution design document agreed with end customer from the engineering and technical team. The
program manager and technical team review the solution design document and confirm the order ID
requirement in the system for the sales team to share with the order entry team to log the orders for a
signed customer order form (COF). The program manager will initiate the service delivery for these
order IDs logged in to the system for these services. Once services are ready for customer delivery,
a technical team will share the customer portal with the end customer and provide training to the
teams at the customer end use the required resources for cloud, compute and storage uses. Along
with the services mentioned above, customers can access the usage and billing information in the
customer portal. Moreover, the program manager is to share the project closure document, including
the information about the services, reference IDs to log the trouble ticket with the supplier’s 24/7
support team and billing start date for customer acceptance

Along with an explosive growth in mobile applications and the emergence of the concept of cloud computing, in mobile cloud computing (MCC) has been familiarized as a potential technology for mobile users. Employing MCC to enable mobile users to realize the benefits of cloud computing in an environment friendly way is an effective strategy to meet today's industrial demands. With the ever-increasing demand for MCC technology, energy efficiency has become extremely relevant in mobile cloud computing infrastructure. The concept of mobile cloud computing offers low cost and high availability to the mobile cloud users on pay-per-use basis. However, the challenges such as resource management and energy consumption are still faced by mobile cloud providers. If the allocation of the resources is not managed in a secure manner, the false allocation will lead to more energy consumption. This article demonstrates the importance of energy-saving mechanisms in cloud data centers and elaborates the importance of the "energy efficiency" relationship to promote the adoption of these mechanisms in practical scenarios. The utilization of resources are being maximized by minimizing the energy consumption. To achieve this, an integrated approach using Cuckoo Search (CS) with Artificial Neural network (ANN) is presented here. Initially, the Virtual Machines (VMs) are sorted as per their CPU utilization using Modified Best Fit Decreasing Approach (MBFD). This suffers from the increase in Service Level Agreement (SLA) violation along with many VM migrations. If the migration is not done at an appropriate host, which can hold the VM for long, Service Level Agreement Violation (SLAV) will be high.

Traditional internet QoS protocols like RSVP cannot be easily migrated to the wireless environment due to the error-prone nature of wireless links and the high mobility of mobile devices. The Internet Engineering Task Force (IETF), the body responsible for guiding the evolution of the Internet, provides the definition as given below: A mobile ad hoc network (MANET) is an autonomous system of mobile routers (and associated hosts) connected by wireless links. The routers are free to move randomly and organize themselves arbitrarily; thus, the network's wireless topology may change rapidly and unpredictably. Such a network may operate in a stand-alone fashion, or may be connected to the larger Internet. QoS is usually defined as a set of service requirements that needs to be met by the network while transporting a packet stream from a source to its destination. The network is expected to guarantee a set of measurable pre-specified service attributes to the users in terms of end-to-end performance, such as delay, bandwidth, probability of packet loss, delay variance (jitter), etc.

MCC integrates cloud computing services into the mobile environment
that helps users to improve performance by utilizing battery life and
storage of devices. When mobile data is stored on cloud rather than in mobile
phone storage then less memory and less battery will be consumed by mobile
phone and it will helps to increases the performance of data transmission but at
same time it violates security of data. As data is transmitted from mobile to
cloud at the mean time there are lots of attackers presented in open environment
that may access or harm the data. To overcome this kind of hazards it is
necessary to propose a mechanism that provides secure data transmission in
MCC. In this paper an attempt has been made to perform assessment on different
security threats and their prevention models with different scenarios. This paper
is divided into six sections. Section 1 presents introduction of mobile cloud
computing (mcc), Sect. 2 covers deployment models of mcc, in Sect. 3 service
models of mcc has been discussed, Sect. 4 presents different kinds of attacks in
mcc environment, in Sect. 5 covers related work of different research papers that
presents security issues and detection techniques in mcc, in Sect. 6 conclusion of
paper has been discussed.

Wireless Sensor Network is a type of wireless network which consists of a collection of tiny device called sensor node. Wireless Sensor Network is one of the rapidly developing areas. Applications of Wireless Sensor Network includes remote environmental monitoring, target tracking, etc. Various algorithms are proposed in 2D for location tracking which provides accuracy but in the real world, we require all the three planes for correct estimation and more accuracy in localization. The 2D works on flat terrain but we need to position WSN in harsh terrain also, so we need an algorithm in 3D that provide better accuracy and decrease the error of estimation and provide a real world view also. The goal of our survey is to present the localization techniques of node.

Tracking of mobile node in WSNs (Wireless Sensor Networks) is an active topic of research and many techniques in WSNs have been proposed. Among the proposed techniques, the popular approach is RSS (Received Signal Strength) and is useful in estimating the distance because it is simple and no extra hardware is required. In this paper, a method that uses RSSI approach is presented to locate the position of mobile node (node that is moving in WSN in Static 2D and Dynamic 2D environment and are not aware of its position in the network) among the other Positioned Nodes or Anchor Nodes in the network. The distance between mobile node and the Anchor Node is estimated by measuring the RSSI (received signal strength indicator). Anchor Nodes are positioned at the vertices of square and mobile node is moving randomly inside the square. The goal is to track the location of mobile node by applying Heron's Formula on the triangles formed inside the square.

In this we propose a new method to reduce noise in digital image. Image corrupted by Gaussian Noise is still a classical problem. In images to reduce the noise or to improve the quality of image peak signal to noise ratio (PSNR) is compared. Higher the PSNR better the quality of the image.In this paper we explain the method curvelet Transformation using log gabor filter Experimental results show that our method gives comparatively higher peak signal to noise ratio (PSNR), are much more efficient and have less visual artifacts compared to other methods.

Cloud computing gives part of advantages to endeavors to offload their information and software services to cloud administrations by saving them lot of money that must be spent on foundation setup cost. Despite that, while offloading the information privacy and protection is a vital concern. Correspondingly for example when the emergency clinics and medicinal services association transfer their patient's subtleties to cloud and when the information is included, it will influence the protection of the patients. So privacy is a vital concern while offloading the information to cloud. Most of solutions for privacy depend on encryption and information to be offloaded is encoded and put away in cloud. Lots of encryption techniques like cryptography, symmetric key etc. methods are used for encrypting the information before uploading to cloud. However, the reaction in this encryption system is that, the encrypted information isn't structure preserving and it is not suitable for ranking or searching. To solve the complications of this searching and ranking due to disordering a homomorphism encryption based mechanism is proposed but this solution also suffers from the problem of integrity attacks on result. So this paper discussed the enhancement of the homomorphism encryption based mechanism by solving the integrity problems effectively.

Mobile cloud computing is a rapidly evolving technology these days and it faces major problems of load imbalance due to the high demand for mobile applications. There are many techniques to solve the problem, but the user can improve load by using a more optimized solution. This research deals with the VM allocation and migration by means of location awareness. The research paper also presents a user authentication and server load management system to reduce the overload of the server. A captcha based authentication mechanism is also presented for user verification. The concept of Feedback is also introduced for the mobile servers. This concept makes the selection of mobile server for the job list. ANN (Artificial neural network) is used for location awareness judgment. ANN is a machine learning approach, which is used to minimize the human effort and also minimize the processing time to allocate job to an accurate server with minimum SLA violation. MBFD (Mobile best fit decreasing) algorithm is used for the VM allocation and selection policy. This research has considered SLA (Service level agreement) violation and energy consumption to compute the performance of the work with an aim of reducing energy consumption with maximized resource efficiency. The proposed work model is also compared with the work presented by Xiong in the same area.

MCC (Mobile cloud computing) is a growing technology which obtained enhanced popularity due to the production and large-scale compilation of personal individual data. Nevertheless, novel security problems occur while MCC provides big data analysis with management services. MCC combines the cloud computing into the smart phone environment and hence overcome the barrier such as battery life, storage and bandwidth. In this paper, we are providing the survey of MCC that is useful to the reader to understand the definition, general overview. The advantages, challenges, and security issues are discussed. The communication protocol named as end to end along with their two types viz. TCP/IP (Transmission control protocol/internet protocol) with UDP (User datagram protocol) protocols are presented along with their properties, limitations and challenges. The concept of load balancing used in MCC is also discussed. At the last, the results analysis is given on the basis of two parameters named as energy consumption and resource utilization for different load condition.

Smartphone devices have occupied an indispensable place in human life. These devices
have some restrictions, like short lifetime of battery, imperfect computation power,
less memory size and unpredictable network connectivity. Hence, a number of methods
previously presented to decrease these restrictions as well as increase the battery
lifespan with the help of offloading strategy. This manuscript proposes anewenhancing
mobile data security using red panda optimized approach with chaotic fuzzy encryption
in mobile cloud computing (RPO-CFE-SMC) to offload intensive computation
tasks from mobile device to the cloud. The proposed model utilizes a red panda optimization
algorithm (RPOA) to scale dynamically the offloading decision under energy
consumption, CPU utilization, execution time, memory usage parameters. Before the
work is transferred to the cloud, an innovative security layer is applied for encrypting
the data using AES chaotic fuzzy encryption (CFE) technology. The proposed
RPO-CFE-SMC method provides 20.63%, 25.25%, 25.28%, and 32.47% lower encryption
time and 23.66%, 24.25%, and 26.47% lower energy consumption compared with
existing EFFORT-SMC, EESH-SMC, and CP-ABE-SMC models respectively. In conclusion,
the simulation results prove that the improved efficiency of proposed model in
offloading computation to the cloud with enhanced data protection using chaotic fuzzy
encryption.

Cloud computing is a promising new technology that is revolutionizing the old Internet computing paradigm and the entire IT sector. Customers and many firms, such as Apple, Google, Facebook, and Amazon, are increasingly adopting mobile cloud computing technology. Because of the rapid advancements in wireless access technologies, cloud computing is expected to grow in the mobile environment. These mobile apps are based on mobile cloud computing principles and methodologies. Users can store their data remotely and access high-quality on-demand cloud apps in the Mobile Cloud environment, eliminating the need to purchase and maintain local hardware and software. These data security vulnerabilities can be remedied with sound data processing. While storing data on the cloud, the cloud service provider can secure the data by using encryption and decryption techniques. This paper suggested encryption and decryption methods for safeguarding data in the cloud. Due to the encrypted format, confidential data cannot be accessed by an unauthorized person or machine.