Partial sharing allows providers to possibly pool a fraction of their resources when full pooling is not beneficial to them. Recent work in systems without sharing has shown that redundancy can improve performance considerably. In this paper, we combine partial sharing and redundancy by developing partial sharing models for providers operating multi-server systems with redundancy. Two M/M/N queues with redundant service models are considered. Copies of an arriving job are placed in the queues of servers that can serve the job. Partial sharing models for cancel-on-complete and cancel-on-start redundancy models are developed. For cancel-on-complete, it is shown that the Pareto efficient region is the full pooling configuration. For a cancel-on-start policy, we conjecture that the Pareto frontier is always non-empty and is such that at least one of the two providers is sharing all of its resources. For this system, using bargaining theory the sharing configuration that the providers may use is determined. Mean response time and probability of waiting are the performance metrics considered.

Increasing content consumption by users and the expectation of a better Internet experience requires Internet service providers (ISPs) to expand the capacity of the access network continually. The ISPs have been demanding the participation of the content providers (CPs) in sharing the cost of upgrading the infrastructure. From CPs' perspective, investing in the ISP infrastructure, termed as public investment, seems rational as it will boost their profit. However, the CPs can alternatively invest in making content delivery more efficient, termed as private investment, as it also boosts their profit. Thus, in this work, we investigate this trade-off between public and private investment of the CPs for a net-neutral ISP. Specifically, we consider centralized decision and non-cooperative forms of interaction between CPs and an ISP and determine the optimum public and private investments of the CPs for each model. In the non-cooperative interaction, we find that at most one CP contributes to the public infrastructure, whereas all invest in their private infrastructure.

The water cycle around the globe is significantly impacted by the moisture in the soil. However, finding a quick and practical model to cope with the enormous amount of data is a difficult issue for remote sensing practitioners. The traditional methods of measuring soil moisture are inefficient at large sizes, which can be replaced by remote sensing techniques for obtaining soil moisture. While determining the soil moisture, the low return frequency of satellites and the lack of images pose a severe challenge to the current remote sensing techniques. Therefore, this paper suggested a novel technique for Soil Moisture Retrieval. In the initial phase, image acquisition is made. Then, VI indexes (NDVI, GLAI, Green NDVI (GNDVI), and WDRVI features) are derived. Further, an improved Water Cloud Model (WCM) is deployed as a vegetation impact rectification scheme. Finally, soil moisture retrieval is determined by the hybrid model combining Deep Max Out Network (DMN) and Bidirectional Gated Recurrent Unit (Bi-GRU) schemes, whose outputs are then passed on to enhanced score level fusion that offers final results. According to the results, the RMSE of the Hybrid Classifier (Bi-GRU and DMN) method was lower (0.9565) than the RMSE of the Hybrid Classifier methods. The ME values of the HC (Bi-GRU and DMN) were also lower (0.728697) than those of the HC methods without the vegetation index, the HC methods without the presence of water clouds, and the HC methods with traditional water clouds. In comparison to HC (Bi-GRU and DMN), the HC method without vegetation index has a lower error of 0.8219 than the HC method with standard water cloud and the HC method without water cloud.

Content delivery networks (CDNs) have been providing the key engineering and economic mediation between content providers (CPs) and Internet service providers (ISPs) in content delivery over the Internet. They significantly improve the quality of service experience for today’s Internet traffic. We model the CDN as a business-to-business platform that provides caching and other services in the Internet content delivery chain between the CPs and the ISPs. The CPs and ISPs that subscribe to the CDN receive a traffic boost relative to their base traffic and in return the CDN prescribes a subscription charge to the CPs, and to the ISPs. We assume that the CDN provides its service without price or quality differentiation between the CPs (or between the ISPs). In this setting we analyze the revenue maximizing prices of the CDN on the two sides of the platform, and its effect on the connection structure on the two sides. We first consider the oligopoly model, where we formulate a full information, leader-follower game. The CDN is the leader and sets the subscription prices for the CPs and the ISPs. The ISPs and CPs are the followers and they make the binary decision of subscribing to the CDN or not. We extend this model to a retail CP market, where the CDN determines the revenue maximizing price using a heuristic and the CPs make the subscription decision. Using extensive numerical analyses, we show that the CDN will always provide sufficient resources to the CPs and that the revenue maximizing price will essentially price out the CPs and ISPs that have a low monetization capability.

The nonpopulation conserving SIR (SIR-NC) model to describe the spread of infections in a community is studied. Unlike the standard SIR model, this does not assume population conservation. Although similar in form to the standard SIR, SIR-NC admits a closed form solution while allowing us to model mortality and also provides a different, and arguably a more realistic, interpretation of model parameters. Numerical comparisons of this SIR-NC model with the standard, population conserving, SIR model are provided. Extensions to include imported infections, interacting communities, and models that include births and deaths are presented and analyzed. Several numerical examples are also presented to illustrate these models. A discrete time control problem for the SIR-NC epidemic model is presented in which the cost function depends on variables that correspond to the levels of lockdown, the level of testing and quarantine, and the number of infections. We include a switching cost for moving between lockdown levels. Numerical experiments are presented.

Coded delivery has been found to improve content delivery by reducing the data transmitted over a broadcast network. The existing works are mostly theoretical, and do not focus on building coded delivery systems for the wireless edge, especially the WiFi edge. In this paper, we first analyze the potential gains of coded delivery that employs index coding at the WiFi edge. This includes designing a system model and the algorithms therein to study the gains of coded delivery. We also compare the gains due to coding with the gains due to caching. The algorithms include segment coding algorithm at the WiFi AP and a cache replacement policy (LFU-Index) at the end user. The system model is then used as the basis to design and implement Wi-Cache, a coded delivery system at the WiFi edge. Coded delivery in Wi-Cache specifically focuses on improving HTTP based video streaming to WiFi clients. The decoding module at the end user for the coded delivery is implemented as a browser plugin that does not require device side configuration changes. We also present the effect of variable and fixed length video segment size on the perceived performance of video streaming when coded delivery is used.

Alzheimer's disease is a degenerative disease in which brain cells die and deteriorate. It is the most prevalent reason for dementia, which is defined as a progressive decrease in thinking, conduct, and social skills that impairs a person's capacity to operate independently. Although it is fatal the early diagnosis of Alzheimer's can be extremely helpful. Our main aim is to help with the diagnosis of this disease in its early stages using the VGG16 classifier which is a convolutional neural network (CNN) that is 16 layers deep. The dataset consists of MRI images of the brain. Data augmentation is done to significantly increase the diversity of data available and Data pre-processing helps to enhance the overall truthfulness of the proposed approach.

We analyze the effect of sponsored data when Internet service providers (ISPs) compete for subscribers and content providers (CPs) compete for a share of the bandwidth usage by customers. Our model is of a full information, leader-follower game. ISPs lead and set sponsorship prices. CPs then make the binary decision of sponsoring or not sponsoring their content on the ISPs. Lastly, based on both of these, users make a two-part decision-choose the ISP to subscribe to, and amount of data to consume from each CPs through the chosen ISP. User consumption is determined by a utility maximization framework, sponsorship decision is determined by a non-cooperative game between CPs, and ISPs set their prices to maximize their profit in response to prices set by competing ISP. We analyze the dynamics of the prices set by ISPs, the sponsorship decisions of CPs, the market structure therein, and surpluses of the ISPs, CPs, users. This is the first analysis of the effect sponsored data in the presence of ISP competition. We show that inter-ISP competition does not inhibit ISPs from extracting a significant fraction of CP surplus, leaving CPs no better off (and sometimes worse off) as compared to the scenario where data sponsoring is disallowed. Moreover, ISPs often have an incentive to significantly skew the CP marketplace in favor of the most profitable CP.

In 21st century due to the advancement in technology and digitalization of healthcare networks, cyber attacks on these networks have advanced and are colossal. The need for protecting healthcare industry from such malice is undeniable. Healthcare information is at risk from malicious actors. Improvements in the state of information security and privacy in the industry are critical to the broad adoption, utilization and confidence in health information systems, medical technologies and electronic exchanges of health information. In this paper a survey on different types of most advanced attacks on healthcare industry and the damage they cause is discussed. Existing approaches to protect healthcare networks is highlighted and a framework for using Next Generation Firewall to detect and prevent cyber attacks is proposed. Additionally configuring the NGFW with a unique hospital network architecture is discussed. The need for an NGFW, its advantages and configuration of such a system is illustrated. Due to rise in road accidents, it has now become necessary to generate a system to limit accidental deaths. To keep a tab on the operators some tollbooths employ a system using fibre optic sensors to automatically classify a vehicle in the background and tally the results with the manual entries. However this system is expensive complicated and requires high maintenance. We aim to study the various systems that can be used to replace such a system with a cheaper and efficient alternative.

We use a queuing model to study the spread of an infection due to interaction among individuals in a public facility. We provide tractable results for the probability that a susceptible individual leaves the facility infected. This model is then applied to study infection spread in a closed system like a large campus, community, and model the interaction among individuals in the multiple public facilities found in such systems. These public facilities could be restaurants, shopping malls, public transportation, etc. We study the impact of relative timescales of the Close Contact Time (CCT) and the individuals' stay time in a facility on the spread of the virus. The key contribution is on using queuing theory to model time-spread of an infection in a closed population.

Challenges in the military, environment, medical, industrial, home, traffic applications, and agriculture extend the scope of Wireless Sensor Networks.Data security over wireless networks is a challenge because of the presence of malicious and non-malicious users, whose purpose is to intercept communication or prevent the transmission of data by real users to perform data theft.To improve the location privacy in geographical routing, a hash-based location privacy-preserving scheme and fake source identification in grid-based geographical routing protocol in WSN are presented.In the SLPGR approach, SHA-256 hash encoding is implemented which hides the location information from attackers.The proposed fake source identification guarantees that the fake source and real source nodes are situated on different quadrants and have enough distance between them.The Findings indicate that the SLPGR model's packet delivery ratio is further 278 % enhancement contrast to the tree-based diversionary routing, and more than 38 % compared to the CASER random walking system.The safety duration of the proposed method increases approx.13% more than the tree-based diversionary routing and 11% more than CASER random walk routing.Energy consumption of the proposed method is lower by 3 times than the tree-based diversionary routing method, 1.4 times lower than CASER random walk routing.The comparative analysis of the SLPGR method shows 3 times lesser delivery miss ratio than tree-based devolutionary routing and 2.6 times lesser delivery miss ratio than CASER routing scheme.

Caching content close to the end users, e.g., at cellular base stations (BSs), WiFi access points (APs), and end user devices is known to improve efficiency and effectiveness of content delivery. This motivates the development of caching-as-a-service where edge networks and devices provide storage capacity to content providers, and enable them to strategically populate these caches to improve user experience in the targeted network. In this paper, we describe Wi-Cache, a prototype for providing caching-as-a-service at the WiFi edge. Wi-Cache is an SDN (Software Defined Networking) based distributed content caching system at the WiFi edge that uses storage at the APs for caching content. Wi-Cache caches content on wireless APs and delivers them to mobile clients when they are requested. It allows content providers to have fine-grained control over the AP-caches and also execute efficient content placement and delivery algorithms at the WiFi edge using a set of APIs that are provided by Wi-Cache. We also show the effectiveness of the Wi-Cache system using an extensive set of experiments.

In Earth there large varieties of planet consisting of number of many unknown and known species. Recognizing flora is ability to identify the plant species from the photographers and provide the medicinal information along with the diseases that can be cured by the plants it is an intelligent system. Creating a Tool that Identify the plant by data of certain characteristics features of Leaves. Comparison between standard data and recorded data is done based on predefined parameters. This will also help us to determine the medicinal values that particular plant has in by Classification based on the Characteristics .This identification should be automated as this process was done by human and every person could not identify accurately even if he identify correctly he could not be efficient .So with the help of the expert system can be designed .

Fetching different parts of the same content (file) simultaneously through multiple network paths has been found to improve content delivery. There are several application layer programs that use this technique to improve the perceived performance at the end users. However, these applications use multiple sockets (multiple connections) at the transport layer, which has several disadvantages. Also, the existing transport layer protocols that allow content delivery over multiple network paths over a single transport layer connection (e.g., MPTCP) are limited to content delivery from a single source. With the availability of content across distributed content servers, there is a need for a transport layer protocol that provides the ability to deliver content from these distributed sources over a single transport layer connection. In this paper, we design and implement a multi-source transport control protocol (MSTCP) that can be used to deliver content from a distributed source to a client application over a single transport layer connection. A prototype implementation and preliminary performance measures showing the effectiveness of MSTCP are also presented.

Congestion externalities are a well-known phenomenon in transportation and communication networks, healthcare etc. Optimization by self-interested agents in such settings typically results in equilibria which are sub-optimal for social welfare. Pigouvian taxes or tolls, which impose a user charge equal to the negative externality caused by the marginal user to other users, are a mechanism for combating this problem. In this paper, we study a non-atomic congestion game in which heterogeneous agents choose amongst a finite set of heterogeneous servers. The delay at a server is an increasing function of its load. Agents differ in their sensitivity to delay. We show that, while selfish optimisation by agents is sub-optimal for social welfare, imposing admission charges at the servers equal to the Pigouvian tax causes the user equilibrium to maximize social welfare. In addition, we characterize the structure of welfare optimal and of equilibrium allocations.

An SI1 SI2 S model represents the opinion dynamics for two opposing opinions over a social network. Two controllers with budget constraints, each representing one of the two opinions, wish to maximize a function of the number of nodes adopting their opinion at the end of a campaign that runs for a fixed duration. We determine the Nash control strategies for both the controllers and first prove a key structural result on these strategies that gives us insights on how campaigns should distribute their effort and ad spend. Next, via extensive simulation studies, we show that not being strategic may lead to a significant loss of effectiveness. We also observe that the relative values of the budgets of the two controllers are more significant than the absolute values of the budgets. Further, we study the allocation of budget across the duration of the campaign by the Nash strategies.

We consider a system consisting of multiple sensors that send updates to a monitoring station via a shared communication channel. The focus is on designing scheduling policies to minimize the time-average of the weighted sum of the Age-of-Information of the sensors. We consider multiple channel models (i.i.d./Markov) and multiple information settings (CSI/delayed CSI/no CSI) and show that the scheduling problem is indexable for all settings considered. In addition, we compute the Whittle index in closed form for some of the settings. Via simulations, we show that Whittle Index based scheduling policies either outperform or match the performance of the best-known policy for all the settings studied.

Video content delivery at the wireless edge continues to be challenged by insufficient bandwidth and highly dynamic user behavior which affects both effective throughput and latency. Caching at the network edge and coded transmissions have been found to improve user performance of video content delivery. The cache at the wireless edge stations (BSs, APs) and at the users' end devices can be populated by pre-caching content or by using online caching policies. In this paper, we propose a system where content is cached at the user of a WiFi network via online caching policies, and coded delivery is employed by the WiFi AP to deliver the requested content to the user population. The content of the cache at the user serves as side information for index coding. We also propose the LFU-Index cache replacement policy at the user that demonstrably improves cache hit and index coding opportunities at the WiFi AP for the proposed system. Through an extensive simulation study, we determine the gains achieved by caching and index coding. Next, we analyze the tradeoffs between them in terms of data transmitted, latency, and throughput for different content request behaviors from the users. We also show that the proposed cache replacement policy performs better than traditional cache replacement policies like LRU and LFU.