**2.1 SDN-based optical network**

*Telecommunication Systems – Principles and Applications of Wireless-Optical Technologies*

fog nodes have limited storage and computing power.

virtual frictionless fashion by using the optical network elements. It has provided new ways for various business applications to move over the latest technologies such as big data analytics, machine learning, etc. in the era of the 5G network. Fog computing is a new distributed architecture which brings computing, storage, and networking services closer to the proximity of the end user [3]. As compared to the traditional cloud computing techniques, it processes real-time applications and data at the edge with minimum latency, minimum network congestion, and lower energy consumption which are the key demand of many industries such as manufacturing, e-health, education, oil and gas, smart cities, smart homes, and smart grids [4]. Fog nodes aggregate the computing resources of edge devices to perform the critical data-sensitive computations where the data of analysis part is directly sent to the cloud for further processing because traditional

The integration of fog computing and PON is an inexpensive, scalable, and simple technology to provide a most promising solution for building e-learning-based smart educational applications [5]. The dynamic capabilities of SDN combined with the state-of-the-art optical technologies have the ability to modernize the optical transport network through its primary feature, i.e., programmability [6]. The purpose of this chapter is to explore efficient techniques to combine SDN-based optical technology at different levels of design and development of smart VR-based applications.

**2. Utilization of optical resources in cloud/fog computing environment**

In order to handle real-time and bandwidth-intensive applications, fog leverages the computing resources of the SDN-based optical network. **Figure 1** shows that the Optical-Fog layer [7] uses ONUs in the middleware of the cloud and IoT layer. In a typical PON channel with multiple OLTs, each OLT is connected with multiple ONUs (16–256) [8]. The Optical-Fog layer is designed by using their residual processing, storage, and interconnection capabilities. It can enable fast service provisioning, dynamic service restoration, network automation, and network optimization at different layers of the underlying network infrastructure. It makes optical network

**170**

**Figure 1.**

*Utilization of optical resources in cloud/fog computing environment.*

Presently, SDN is supporting wide area network to deal with many more technologies for delivering several benefits. It has adopted a hierarchical approach in which domain controllers collect information and delegate the control (real time) over the network layers and geographic clusters to support applications and provide higher levels of service orchestrations. Initially, SDN was used in data centers for separating the data plane, control plane, and management plane from each other [9]. The interface like OpenFlow is used by the centralized controller to deliver computing infrastructure for making better communication. While applying this concept to the optical network, optical domain controller (ODC) plays an important role. As shown in **Figure 2**, it provides a more programmatic and abstract view of the underlying optical network through the northbound interface [10]. The programming feature of SDN makes it capable of fulfilling customized demands for manipulating network infrastructure. To handle real-time, bandwidth-intensive applications, fog uses the computing resources of the SDN-based optical network.

The SDN-based optical network infrastructure fulfills the demand of increasingly high-performance and network-based applications with flexibility and efficiency. The key security issues in fog/cloud computing over optical network lies at both downstream and upstream channels of PON. PON uses broadcasting in the downstream channel which is prone to eavesdropping attacks where an attacker can modify the behavior of ONUs at its media access control (MAC) layer. On the other hand, the traffic in the upstream channel is only visible to the OLT rather than other ONUs that can also be exploited for attacks. In PON network, OLT uses time division multiplexing access (TDMA) that provides sharing of the upstream channel among


#### **Table 1.**

*List of acronyms.*

ONUs [11]. It assigns static or dynamic nonoverlapping time slots to connected ONUs. Here, OLT and all connected ONUs are well synchronized that result in the collisionfree transmission of the traffic or data frames. In the security aspects of PON, more research work is required that can restrict the ONUs to send data frames outside of their preassigned time-slots. In case if a malicious ONU intends to send data frames outside its preassigned time slot, the collision can encounter with the data-frames of other ONUs that degrade the quality of service (QoS) of the optical channel.

To ensure QoS and quality of experience (QoE) to the end-user for various real-time CPS-based applications, Optical-Fog layer is utilized. To handle real-time processing, this layer uses the optical network resources by creating *OpticalFogNode.* The optical network can effectively realize the interconnected optical resources (PON, OLTs, and ONUs) across the 5G network. It provides ultralow delay and less energy consumption for IoT devices and uses the majority of the computing resources of the optical layer rather than the cloud layer.

### **2.2** *OpticalFogNode* **for implementing CPS system**

CPS enables the integration of cyber components such as sensors, computational and control units, and network devices into the physical components (such as objects, end-users, and infrastructures) by connecting them to the Internet and each other. It also has shown tremendous progress in many fields like communication, healthcare, education, manufacturing, robotics, transportation, military, etc. It has also encouraged many innovative and ever-growing projects in the application domain of cloud and fog computing. CPS requires a novel, highly distributed, secure fog computing infrastructure in the heterogeneous network for strengthening its position for the mobile and wireless network in the new 5G era [12]. It can provide unified and cost-effective computing services for smart cities, vertical industries, and IoTs at the extreme edge of the new 5G network.

Further, the concept of an *OpticalFogNode* is proposed that supports low-cost and on-demand access to the computing infrastructure of the Optical-Fog layer in the 5G network. The main challenge is to run the CPS-based applications on the *OpticalFogNode.* The optical network virtualization (ONV) and SDN provide a

**173**

*Role of Optical Network in Cloud/Fog Computing DOI: http://dx.doi.org/10.5772/intechopen.84404*

novel solution to deploy *OpticalFogNode* at the edge of the network. All free available resources (FARs) of the optical elements are grouped together to form an *OpticalFogNode* with the computing capabilities like processor, memory, and bandwidth. ONV converts the free available physical resources of the optical network elements into the virtual resources as infrastructure-as-a-service (IaaS) model. Initially, each submitted task is categorized as CBS-based or non-CPS-based task on the basis of requested resources in terms of processing power, storage, bandwidth, acceptable security level, etc. The Optical-Fog manager can dynamically reconfigure the *OpticalFogNode* which provides the desired reliability and QoS for the CPS. An algorithm is proposed that identify all possible created *OpticalFogNode* on the SDN path and assign them CPS-based tasks for further processing. The non-CPS-based tasks are directly sent to the cloud layer only if the resources of *OpticalFogNode* are not free.

In the proposed algorithm, the resources required by the new task are evaluated and then allocated on the *OpticalFogNode.* This node is scalable to provide the

required computing resources dynamically by using the concept of ONV.

*Role of Optical Network in Cloud/Fog Computing DOI: http://dx.doi.org/10.5772/intechopen.84404*

*Telecommunication Systems – Principles and Applications of Wireless-Optical Technologies*

ONUs [11]. It assigns static or dynamic nonoverlapping time slots to connected ONUs. Here, OLT and all connected ONUs are well synchronized that result in the collisionfree transmission of the traffic or data frames. In the security aspects of PON, more research work is required that can restrict the ONUs to send data frames outside of their preassigned time-slots. In case if a malicious ONU intends to send data frames outside its preassigned time slot, the collision can encounter with the data-frames of

CPS enables the integration of cyber components such as sensors, computational

and control units, and network devices into the physical components (such as objects, end-users, and infrastructures) by connecting them to the Internet and each other. It also has shown tremendous progress in many fields like communication, healthcare, education, manufacturing, robotics, transportation, military, etc. It has also encouraged many innovative and ever-growing projects in the application domain of cloud and fog computing. CPS requires a novel, highly distributed, secure fog computing infrastructure in the heterogeneous network for strengthening its position for the mobile and wireless network in the new 5G era [12]. It can provide unified and cost-effective computing services for smart cities, vertical

Further, the concept of an *OpticalFogNode* is proposed that supports low-cost and on-demand access to the computing infrastructure of the Optical-Fog layer in the 5G network. The main challenge is to run the CPS-based applications on the *OpticalFogNode.* The optical network virtualization (ONV) and SDN provide a

other ONUs that degrade the quality of service (QoS) of the optical channel. To ensure QoS and quality of experience (QoE) to the end-user for various real-time CPS-based applications, Optical-Fog layer is utilized. To handle real-time processing, this layer uses the optical network resources by creating *OpticalFogNode.* The optical network can effectively realize the interconnected optical resources (PON, OLTs, and ONUs) across the 5G network. It provides ultralow delay and less energy consumption for IoT devices and uses the majority of the computing

resources of the optical layer rather than the cloud layer.

industries, and IoTs at the extreme edge of the new 5G network.

**2.2** *OpticalFogNode* **for implementing CPS system**

**172**

**Figure 2.**

*SDN-based optical network.*

novel solution to deploy *OpticalFogNode* at the edge of the network. All free available resources (FARs) of the optical elements are grouped together to form an *OpticalFogNode* with the computing capabilities like processor, memory, and bandwidth. ONV converts the free available physical resources of the optical network elements into the virtual resources as infrastructure-as-a-service (IaaS) model. Initially, each submitted task is categorized as CBS-based or non-CPS-based task on the basis of requested resources in terms of processing power, storage, bandwidth, acceptable security level, etc. The Optical-Fog manager can dynamically reconfigure the *OpticalFogNode* which provides the desired reliability and QoS for the CPS. An algorithm is proposed that identify all possible created *OpticalFogNode* on the SDN path and assign them CPS-based tasks for further processing. The non-CPS-based tasks are directly sent to the cloud layer only if the resources of *OpticalFogNode* are not free.

In the proposed algorithm, the resources required by the new task are evaluated and then allocated on the *OpticalFogNode.* This node is scalable to provide the required computing resources dynamically by using the concept of ONV.

If the computing resources of *OpticalFogNode* are already occupied, then there are two options to execute the task on the basis of its preference. If the requested new task is a non-CPS task, it can be directly allocated to the cloud. Otherwise, CPS-centric task can be executed.


Further, this layer uses the SDN-based controller for optimizing the distribution of the flow among various redundant paths. In order to increase the QoS, the shortest path is chosen that minimizes the delay. In the optical network in the 5G environment, the *OpticalFogNode* has a flow table which is used to match the routing information of the received packet in the path. If there is no entry found in the flow table, the received packet is forwarded to the SDN controller for finding the shortest path so that the particular packet can be forwarded. Thus, a new entry is added (once the path is chosen) in the flow table of the *OpticalFogNode* for the coming future packets. Hence, the proposed SDN controller identifies the shortest path with the least congestion among all possible paths.

### *2.2.1 Architecture of OpticalFogNode*

In SDN-based Optical-Fog/cloud network, the key challenge with the deployment of a fog node is to make it secure from the attackers. However, attackers are capable to create malicious programs with the ability to detect and evade their targets in distributed computing environments. **Figure 3** shows that optical network virtualization provides a novel solution to deploy *OpticalFogNode* in the middleware of IoT devices and the cloud rather than deploying at cloud data centers.

SDN technology combined with optical network virtualization allows for running the control logic of each tenant on a virtual SDN controller rather deploying and running at the cloud data centers.

The resources to the proposed *OpticalFogNode* can be provisioned on demand from geographically distributed optical elements specially ONUs. The architecture of *OpticalFogNode* is shown in **Figure 4** where it can be deployed and configured virtually. The architecture has southbound and northbound interface along with SDN controllers which belong to different tenants of *OpticalFogNode* to emulate them for different IoT applications. It has the capability to control optical network elements for processing the configuring demand of different *OpticalFogNode* tenants such as computing resources, topology, address scheme, node mapping options, etc. Hence, virtual *OpticalFogNode* can be created in the form of infrastructure-as-aservice for providing real-time control to each *OpticalFogNode* tenant over its virtual

**175**

**Figure 4.**

**Figure 3.**

each *OpticalFogNode* tenant.

*SDN-based OpticalFogNode architecture.*

*Role of Optical Network in Cloud/Fog Computing DOI: http://dx.doi.org/10.5772/intechopen.84404*

*Deployment scenario of OpticalFogNode at Optical-Fog layer.*

network. In order to form virtual infrastructure, a free-available-resource concept is proposed which uses the freely available resources of the optical network elements that lie at the Optical-Fog layer. Since routers and switches have limited resources, only optical elements such as optical network units and optical line terminals are taken into account for implementing FAR. Optical elements like ONUs and OLTs have their own processing, storage, and interconnection capabilities that are not fully utilized by the present network scenario. Thus, as shown in **Figure 5**, each optical element has some amount of running resources as well as FAR. Our proposed *OpticalFogNode* aggregates those FARs for facilitating the computing capability to

*Role of Optical Network in Cloud/Fog Computing DOI: http://dx.doi.org/10.5772/intechopen.84404*

#### **Figure 3.**

*Telecommunication Systems – Principles and Applications of Wireless-Optical Technologies*

its category as CPS-based or non-CPS-based task.

• *RunningTask* represents the already running tasks.

concept of ONV at the Optical-Fog layer.

path with the least congestion among all possible paths.

*2.2.1 Architecture of OpticalFogNode*

and running at the cloud data centers.

CPS-centric task can be executed.

processing.

• *OpticalFogNodeDC*

*OpticalFogNode.*

If the computing resources of *OpticalFogNode* are already occupied, then there are two options to execute the task on the basis of its preference. If the requested new task is a non-CPS task, it can be directly allocated to the cloud. Otherwise,

• *T* represents the requirements of submitted task for the framework along with

• *OpticalFogNode* is virtual and a dynamically configurable smart node using the

• *TaskToPlaced* all coming task to be allocated to the *OpticalFogNode* for further

Further, this layer uses the SDN-based controller for optimizing the distribution of the flow among various redundant paths. In order to increase the QoS, the shortest path is chosen that minimizes the delay. In the optical network in the 5G environment, the *OpticalFogNode* has a flow table which is used to match the routing information of the received packet in the path. If there is no entry found in the flow table, the received packet is forwarded to the SDN controller for finding the shortest path so that the particular packet can be forwarded. Thus, a new entry is added (once the path is chosen) in the flow table of the *OpticalFogNode* for the coming future packets. Hence, the proposed SDN controller identifies the shortest

In SDN-based Optical-Fog/cloud network, the key challenge with the deployment of a fog node is to make it secure from the attackers. However, attackers are capable to create malicious programs with the ability to detect and evade their targets in distributed computing environments. **Figure 3** shows that optical network virtualization provides a novel solution to deploy *OpticalFogNode* in the middleware

SDN technology combined with optical network virtualization allows for running the control logic of each tenant on a virtual SDN controller rather deploying

The resources to the proposed *OpticalFogNode* can be provisioned on demand from geographically distributed optical elements specially ONUs. The architecture of *OpticalFogNode* is shown in **Figure 4** where it can be deployed and configured virtually. The architecture has southbound and northbound interface along with SDN controllers which belong to different tenants of *OpticalFogNode* to emulate them for different IoT applications. It has the capability to control optical network elements for processing the configuring demand of different *OpticalFogNode* tenants such as computing resources, topology, address scheme, node mapping options, etc. Hence, virtual *OpticalFogNode* can be created in the form of infrastructure-as-aservice for providing real-time control to each *OpticalFogNode* tenant over its virtual

of IoT devices and the cloud rather than deploying at cloud data centers.

*Avail* is a free available resource at the dynamically configured

• *OpticalFogNodeNodeAvail* is a free available resource at the OpticalFog.

**174**

*Deployment scenario of OpticalFogNode at Optical-Fog layer.*

#### **Figure 4.**

*SDN-based OpticalFogNode architecture.*

network. In order to form virtual infrastructure, a free-available-resource concept is proposed which uses the freely available resources of the optical network elements that lie at the Optical-Fog layer. Since routers and switches have limited resources, only optical elements such as optical network units and optical line terminals are taken into account for implementing FAR. Optical elements like ONUs and OLTs have their own processing, storage, and interconnection capabilities that are not fully utilized by the present network scenario. Thus, as shown in **Figure 5**, each optical element has some amount of running resources as well as FAR. Our proposed *OpticalFogNode* aggregates those FARs for facilitating the computing capability to each *OpticalFogNode* tenant.

**Figure 5.** *Free available resource.*

Hence, all FARs of optical network are grouped together to form virtual data centers with computing resources such as processor, memory, and bandwidth. ONV converts the physical resources of optical network elements into the virtual resources as infrastructure-as-a-service (IaaS) model to build virtual honeypots that prevents vulnerability and its identity from the attacker.
