Smart campus: The resources are scarce and are rapidly depleting with an increase in the global population, hence they are limited. Further, it is not advisable to neglect the environmental effect.
Climate change, soil erosion, global warming, acid rain, etc. in the exploration of resources on a large scale. It demands awareness among the consumers, manufacturers, designers, service providers, to develop energy-efficient IoT system for smart cities. In this regard the role of NGOs, educational institutions, think tanks, intellectuals remain vital to promoting green residences or campuses. This can be possible by providing automatic monitoring and control of IoT devices focusing on the economy, energy-efficient, reliability, etc. [18].
1.3.2 The IoT Software Domain
A few of the IoT Software domains are shown in Figure 1.3 and have been explained briefly here.
1.3.2.1 IoT in Cloud Computing (CC)
CC aims to deliver the hardware and software services across a parallel and distributed system. It has three important characteristics such as (a) virtual, (b) dynamic provision on-demand, and (c) negotiation. In this scheme, the hardware and software systems are interconnected dynamically and computerized virtually [19]. This way, the scheme reduces the carbon footprints and emissions besides decreasing the energy consumption appreciably. This can be achieved by transferring a few on-premises applications into the cloud. One of the real-life situations where CC finds its use is on-line marketing in which we procure goods and services without our presence in the shop-floor physically. Further, it reduces unnecessary expenditure on transportation and reduction in greenhouse gas emissions by each individual going to the shop-floor separately. As it is possible in CC to use the resources of the service provider rather than buying expensive equipment or systems for a business, it is economical. The reduction in the cost of using CC may be attributed to the following.
One can include new software, hardware, and system upgrade costs in his/her contract.
The expert data is found in the cloud, thus need to hire or pay the expert staff.
Thus, it reduces energy consumption.
Unnecessary time delays can be avoided.
Some of the other benefits that are offered by CC are security, flexibility, insight, quality control, increased collaboration, disaster recovery, competitive edge, loss prevention, sustainability, etc. The major advantages of CC have been shown in Figure 1.4.
The limitations of CC are briefed below.
Privacy agreement: The user in the CC platform requires the desired privacy and service level agreement before the commencement of the services. It delegates certain responsibilities on both the service provider and the user which needs to be adhered to by both the parties.
Security: The protection of data and the security against pilferage, theft, etc. need to be considered beforehand. While it is provided by the service provider in its periphery, the remote users need to weigh the security system before opting for CC.Figure 1.3 Softwarebased IoT applications.Figure 1.4 The benefits of CC.
Vulnerability: Since each component is easily accessible via the internet, it is likely to be attacked by hackers.
Limited flexibility and control: The uses in CC have limited control over the execution and function of the service provider as per the agreement signed by both parties.
Platform dependencies: The vendor lock-in or implicit dependency creates deep-rooted differences between the user and the service providers. This sometimes poses difficulties for users to migrate to other service providers at will due to additional cost, security, and privacy issues.
Cost: for small businesses or on a small scale, CC cost exceeds the cost due to staffing or hardware procurement.
Types of CC
The commonly employed CC services are briefed below.
Infrastructure as a service (IaS): In this, an external service provider facilitates the user with computer power and disc space via the internet. The users need to have hardware such as CPU, data storage, memory, or network connectivity. Examples of IaS are the Rackspace, Amazon EC2, Windows Azure, etc.
Software as a service (SaS): In this, the user can access the internet-hosted software by browsing. The service provider maintains and controls the software updates and the user has limited control over the configuration settings and the applications. It is mostly suitable for small businesses.
Platform as a service (PaS): It is a crossover between SaS and Ias. In this case, the user rents the operating system, hardware, network capacity, storage, etc. to the service provider. Thus, the user has the desired control over the computing setup, technical aspects, customization, etc. as per his/her need.
1.3.2.2 IoT in Edge Computing (EC)
CC is an efficient mechanism to process the data that reduces at the network edge. New software domains have been developed that are more energy-efficient than CC are the Fog or EC [20, 21]. In EC the computation of the enabling technologies is carried out at the edge of the network. At downstream data, this function is performed using cloud services whereas, at upstream data, the IoT services are carried out.
In EC, the network resources are managed and controlled between the path of cloud data found useful in the case of a smartphone which is considered to be an edge between the body things and the cloud. Similarly, a gateway is an edge between campus things and cloud in green computing, or the cloudlet and the microdata center act as an edge between the cloud and the mobile device. While FC is oriented more towards the infrastructure side, EC is focused on the things-side. Hence, the latter remains an emerging technology at par with CC in the current scenario. The EC requires minimum use of refrigeration and maintenance as it needs a small data center for functioning. Ultimately, the technique remains energy efficient with a reduction in e-waste. The use of EC has reduced the response time to 169 ms as compared to 900 ms required by CC [22]. The hierarchy of EC is shown in Figure 1.5.
EC aims to save bandwidth and to reduce the response time by bringing the data storage and the computation closer to the desired location. It has recently been found to be applied in dealer locators, real-time data aggregators, shopping carts, and insertion engines. It is a computing technology that can deliver nearer to a request zone with low latency. As compared to CC that suits big data analysis, EC performs better in real-time processing of data generated by the users or sensors such as ‘instant data’. EC moves the computation away from data centers towards the edge of the network, thus helps smart things or objects such as network gateways or mobile phones to accomplish the desired services or tasks on behalf of the cloud. On account of this shift, it becomes reliable to facilitate service delivery, content catching, IoT management, and storage with reduced response time and efficient transmission and reception of data.