Abstract – Software Defined Networks can be considered the most important development in Computer Networking in the last decade

January 27, 2019 Critical Thinking

Abstract – Software Defined Networks can be considered the most important development in Computer Networking in the last decade. Deep packet inspection (DPI) technology significantly enhances the security and management of current networks but combined with software-defined networking (SDN), DPI becomes an even more powerful tool that can centralize network policy control and accelerate automation. The conversion from the traditional networks to the SDN network has a significant challenges that need a careful examination. We focus on Improved DPI can provide the detailed data to inform the SDN controller about the state of the network and its traffic flows. This allows SDN to treat the network as a holistic resource rather than a diverse group of devices (e.g. switches, security and other Layer 4-7 elements). Ultimately, connecting SDN and DPI will let network pros apply policy control and automation to the entire network as opposed to individual components or elements. Leveraging a central DPI capability will provide intelligence to all relevant functions (controller, policy, security, etc.) — instead of the current system of each functional box performing its own DPI. So, it became a must to inspect the data in SDN architecture that fit the benefits of central control. KeywordsSDN, DPI, Operator, Open flow, QOS, Control plan , Data plan, application plan Introduction 1.1. The need for a new network architecture The capacity of the current Internet is becoming insufficient to meet the large volumes of traffic patterns delivered by the new services (e.g., mobile devices and content, server virtualization, cloud services, big data), which is generated due to a large number of users, sensors and applications 1,2. Legacy networks built with multiple tiers of static Ethernet switches arranged in a tree structure are unsuitable for the dynamic computing and storage needs of todays. Instead, new networking infrastructures are reqired that will provide high performance, energy efficiency, and reliability. Moreover, they should improve the network speedup, scalability and delivery of many digital services that provide quality of service (QoS) guarantees. Meeting these requirements is impossible with existing network equipment due to their limited capabilities. In addition, to implement network-wide policies and to support any new services, managers today have to configure thousands of network devices and protocols, which makes it difficult to apply a consistent set of QoS, security, and other policies. Networks become more complex with the addition of thousands of network devices that must be configured and managed. integration to network devices is very hard because of The internals differ from vendor to vendor. 1.2. Software-Defined Networking Software-Defined Networking (SDN) 3,4 the main principle is separation where the control plane logic is decoupled from the data plane. SDN is a new approach for network programmability, which refers to the ability to control, change, and manage network behavior dynamically through software .The SDN framework enables centralized control of data path elements independently of the network technology used to connect these devices that can originate from different vendors. The centralized control embeds all the intelligence and maintains a network-wide view of the data path elements and links that connect them. This centralized real time view makes the controller suitable to perform network management functions while allowing easy modifications to the networking functions through the centralized control plane. Fig. 1 describes the SDN architecture illustrating the separation between the applications, control plane and data plane. Applications use the northbound API supported by the control plane to enforce their policies in the data plane without directly interacting with the data plane. The interface between the control and data plane is supported by southbound APIs, where a SDN controller will use these APIs to communicate with the network equipments in the data plane. These equipments are required to support the standardized APIs at this level. SDN makes it possible to manage the entire network through an intelligent vision and provisioning system that enables on-demand resource allocation, self-service provisioning. Thus, the static network can evolve into an extensible vendor-independent service delivery platform capable of responding rapidly to changing business, end-user, and market needs, which greatly simplifies the network design and operation. Then, the devices themselves no longer need to understand and process thousands of protocol standards but simply accept instructions from the SDN controllers. A tangible implementation of the SDN approach is OpenFlow (OF) 5,6. OpenFlow aims to allow providers to reengineer their traffic to test out new protocols in existing networks without disrupting production applications. The key elements of this technology consists of three parts (i) flow tables installed in OpenFlow-aware switches, (ii) a controller installed in a remote host machine, and (iii) an OpenFlow protocol for the controller to talk securely with switches. The OpenFlow approach of splitting the control logic from the forwarding behavior provides a flexible capability for on-the-fly addition and update of several forwarding roles in the data plane. 1.3 Role of DPI The SDN framework enables centralized control of network, more flexible to perform network management functions , easy modifications to the networking functions but still need more info than layer 2-3 need increasingly sophisticated insight into the behavior of subscribers to make better policy decisions and build better services, SDN needs to improve quality of service and Dpi can do this role7 Figure 2 DPI Use Cases in an SDN The needs to create feedback loop in which a stream of real-time information on performance, application use trends, user behavior, congestion events, device trends and much else besides is fed back to the SDN controller. The need to understand what customers are using and doing (using the monitoring and analytics capabilities that are now a part of most DPI software) in order to offer more appropriate and personalized service packages to them. The need to protect networks from spam, viruses, DDoS attacks and harmful or illegal content, using DPI to identify threats relatedly, regulatory drivers such as the requirement for lawful intercept and for parental or enterprise content control systems. The need to identify and manage high-impact applications such as P2P and video streaming traffic in order to both reduce or ameliorate their effects, especially on network congestion, and improve the QoE of applications such as video streaming. Widespread deployment of the 3GPP Policy Control and Charging (PCC) standard, with DPI feeding back information to policy servers to help with decision-making typically the same hardware or software also handles policy enforcement. Figure 3 SDN Challenges Solutions DPI in SDN Architecture DPI usually deployed in traditional network as an embedded it in various network appliances and devices, such as firewalls, SGSN/GGSN, and so on. A major drawback of this approach is the high cost associated with implementing DPI technology many times on different hardware platforms. In addition, the integration between applications is difficult since each vendor may have a specific way of performing DPI and formatting the results. For example, one vendor may classify a flow as Facebook while another vendor may designate it social media. With SDN ,DPI can transfer from being embedded in many network appliances to becoming a shared function hosted on standard servers. This approach lowers the total investment in DPI, since DPI is implemented on fewer machines , and therefore less energy is consumed. furthermore, the integration between different functions and applications using DPI is less complex because it is easier to perform a suitable format for App IDs and metadata. Locating DPI in SDN-based Networks As described before, SDN architecture consists of three layers,including the network applications, control, and node layers. Figure 4 shows the three layers where DPI is likely to be embedded for traffic shaping, subscriber analytics, QoE, and cybersecurity. These deployment scenarios 8 allow DPI information to be shared in the network, which saves CPU and energy costs as application classification is done once instead of several times. Unified DPI simplifies management because all devices would share a similar view of the traffic. Figure 4 Dpi at different layers The three probable deployment scenarios are described in the following Network applications layer DPI software can be embedded in applications running in the network applications layer. However, some application redesign may be needed to minimize the impact of potential bottlenecks created by a long communication path. For instance, part of the traffic flows must be transmitted from the node through the SDN controller to the network application running a DPI engine. After the flow is identified, the application sends policy rules to the node to steer the flow, so only a fraction of the traffic is typically sent from the node to the network application. Given the possibility for delay, this DPI deployment works best for non-time-critical network applications, like analytics. Controller layer DPI software may be deployed in the SDN controller, which may use the network intelligence for its own control services or send it to the network applications layer via the northbound API.The node (e.g., switch, network device) handling the flow sends the first non-empty packet to the SDN controller for L4-L7 analysis, possibly using the OpenFlow protocol . Locating DPI in the controller avoids an increase in the cost of nodes however, portions of the traffic must be duplicated and forwarded from nodes to the controller, which could lead to scalability and performance issues. A distributed controller architecture design can minimize these concerns. Data layer Network nodes can also run DPI software, and after identifying the App ID and metadata, they can either apply a pre-defined policy directly, or send this information to the SDN controller or a network application, and then receive back policies or rules. When the SDN controller is the recipient of the extracted information, it can instruct the node to apply a particular policy after having some sort of dialog with a network application. Afterwards, all subsequent flows of the same type do not require DPI analysis. Compared to the other options, implementing DPI in the node layer minimizes latency RELATED WORK The classical algorithms for exact multiple string matching used for DPI are those of Aho-Corasick 10 and Wu-Manber 11. For regular expression matching, two common solutions are using Deterministic Finite Automata (DFA) or Nondeterministic Finite Automata (NFA) 12, 13. Efficient regular expression matching is still an active area of research 14, 15, 13, 16, 17. There is extensive research on accelerating the DPI process, both in hardware 18, 19, 33 and in software 19, 13. Most software based solutions 19, 13 accelerate the DPI process by optimizing its underlying data structure (namely, its DFA). To the best of our knowledge, no specific design for accelerating DPI in a virtual, consolidated, or NFV environment has been proposed. The only exception is an industrial product of QOSMOS 8, which specializes in protocol classification and does not deal with the general DPI problem. Moreover, no details are disclosed on its implementation. And also Deep packet inspection as service9 its the nearst solution bot it focus on middle boxes that use dpi function ,still costly because it implement a lot of dpi instance inside data plan, it split the work among instances running over different machines. However, a similar concept was studied in the context of virtual IP-lookup, where trie-based data structures are considered 20, 21, 22. This research is not applicable to DPI as the underlying algorithms are significantly different. Figure 5 System Illustration. SYSTEM OVERVIEW This section details the underlying architecture that supports DPI as a service. The main idea is to split dpi service to two main part the first part DPI service scans the packet and logs all detected patterns and send the scan result to the second main part Dpi controller to manage the policy chain .. We assume an SDN environment with a Traffic Steering Application (TSA) (e.g., SIMPLE 23) that attaches policy chains to packets and routes the packets appropriately across the network.(see Figure 5). The DPI Controller DPI service scalability is important since DPI is considered a bottleneck for all Operators to have hall vision . Therefore, we envision that DPI service instances will be deployed at network gateway.The DPI controller is a logically centralized entity whose role is to manage the DPI process across the network and to communicate with the SDN controller to realize the appropriate data plane actions. Logically, the DPI controller resides on top of the SDN controller as in Figure 5. Two kinds of procedures take place between the DPI Controller and dpi instance, The first task of the DPI controller is to write policy and rules for Dpi instance through configuration file . Communication between the DPI Controller and dpi instance is performed using JSON messages sent over a direct (possibly secure) communication channel to receive the result and logs from DPI instance. The DPI controller also make all information about network avalibale at SDN controller thats help TSA to set the policy chain make the decision to the right path forwarding the traffic Usually, the TSA pushes some VLAN or MPLS tag in front of the packet to easily steer it over the network ( 41) ,Dpi controller is also canreceives from the TSA the relevant policy chains (namely, all the sequences of middlebox types a packet should traverse). It assigns each policy chain a unique identifier that is used later to manage the traffic directly between middle boxes like firewalls (FUTURE WORK).Finally, the DPI controller is also responsible for initializing DPI service instances , and advance features that require a network-wide view. Deployment of DPI Instances The DPI controller abstracts the DPI service for the TSA, SDN controller, and the middleboxes. Hence, one of its most important tasks is to deploy and register the DPI instances. the DPI controller should manage the DPI instance resources There might be many considerations for such deployment and in this section we discuss only a few. First, we emphasize that all DPI instances need to be at the gatway of our network to inspect all packets that from and to network or subscriber. The DPI controller will then instruct the TSA to set the right policy chain. Additionally, the DPI controller should manage the DPI instance resources, so that an instance is not overwhelmed by traffic, and therefore, performs poorly. Thus, the DPI controller should collect performance metrics from the working DPI instances and may decide to allocate more instances, to or to migrate flows between instances. DPI INSTANCE IMPLEMENTATION The main target to Dpi instance Examine traffic in real-time to diagnose issues and confirm policy enforcemen, Leverage analytics to identify trends and opportunitie, enabling new services and identifying application quality trends, according to that we use an open sourc Dpi nDPI 24 at Dpi instance. In nDPI an application protocol is defined by a unique numeric protocol Id, and a symbolic protocol name (e.g. Skype). Applications using nDPI will probably use the protocol Id whereas humans the corresponding name. A protocol is usually detected by a traffic dissector written in C, but it can be defined also in terms of protocol/port, IP address (e.g. traffic from/to specific networks), and protocol attributes. For instance the Dropbox traffic is identified by both the dissector for LAN-based communications, and by tagging as Dropbox the HTTP traffic on which the Host header field is set to .dropbox.com, And also nDpi can Handling Encrypted Traffic. the nDPI library includes the detection of over 170 protocols, nDPI contains internally a configuration for many known protocols that are discovered using the above technique. In addition, it is possible to add at runtime a configuration file that further extends the set of detected protocols so that new ones can be defined without changing the protocol dissector. but it can also be further extended at runtime using a configuration file. nDPI users can define protocols not just by adding a new protocol dissector, but also providing a configuration file at runtime.The file format is the following. Format tcpudpport,tcpudpport,…[email protected] tcp81,[email protected] [email protected] tcp860,udp860,tcp3260,[email protected] [email protected] Subprotocols Format hostvalue,hostvalue,…[email protected] [email protected] [email protected] For instance in the previous example, whenever nDPI sees TCP traffic on port 81 or 8181 it tags it as HTTP. The nDPI library inherits some of OpenDPI design, where the library code is used for implementing general functions, and protocol dissection is implemented in plugins. All the library initialization is performed only once at startup, without a runtime penalty when a new packet needs to be dissected. nDPI expects the caller to provide the packet divided in flows (i.e. set of packets with the same VLAN, protocol, IP/port source/destination), and that the packet has been decoded up to layer three. This means that the caller has to handle all the layer-2 encapsulations such as VLAN and MPLS, by leaving to nDPI the task of decoding the packet from the IP layer up. nDPI comes with a simple test application named pcapReader.c that shows how to implement 1 packet classification and provides utility functions for efficient flow processing. Please note that with the advent of CDN (Content Delivery Networks) this is probably the only way of identifying the application protocol, as at any given time the same server (identified with a single IP address) can deliver two different services provided by two customers using the same CDN. As a fallback, nDPI can identify specific application protocols using the IP address. Experimental results According to our Solution we solve the issue we mentioned it before at locating Dpi at SDN , locating Dpi instance at Data layer and separating Dpi controller avoid us of network latency and solve performance and scalability issues because of Duplications traffic if you locate Dpi at control or application layer additionally locating it at network gateway is costly less than locating more Dpi appliance across network at data layer. Figure 6 System Illustration Networklatency at case of Application layer is higher than controller layer and data layer is the less (figure 6) we neglect the processing latency because its aconstant we assume we use the same Dpi at each layer. Future work 1) Planned to integrate with radius traffic to make full mapping to subscriber at Isp operators. 2) making flow table to manage flow traffic between middle boxes (Firewall, IDS,IPS,). conclution Growth of traffic is creating a big challenge for network operators it hard to manage and monitor , SDN makes it easier to manage bandwidth by giving operators the ability to manage network assets from a centralized control point with a global view instead of a decentralized, local view. but it is not enough operators of an SDN still need to be able to identify and analyze , in real-time, the applications and traffic running on their networks This is another challenge facing network operators is insufficient knowledge about the traffic on their networks, DPI have the capability to identify types of traffic (applications) running in the network, in real-time, and to associate that information at an incrementally granular level with other data such as subscriber, device, location and so on, This paper focuses on Deep Packet Inspection and locating Dpi at SDN layers the main idea to split dpi service to two main part the first part DPI service locating at network gateway responsible for scans the traffic and send the scan result to the second main part Dpi controller to manage the policy chain, gives operators greater control over networks carrying traffic for a wide range of services and applications and Giving it more improvement, speed and flexibility in network.. REFERENCES 1 A. Metzger, C.C. Marquezan, Future internet apps the next wave of adaptive service-oriented systems, in ServiceWave, 2011, pp. 230241. 2 G. Ortiz, J. Cubo, Adaptive Web Services for Modular and Reusable Software Development Tactics and Solutions. IGI Global, 2013. 1415. Web. 6 Nov. 2014. HYPERLINK http//dx.doi.org/10.4018/978-1-4666- 2089-6 http//dx.doi.org/10.4018/978-1-4666- 2089-6. 3 N. McKeown, Software-defined networking, INFOCOM keynote talk, April 2009, Rio de Janeiro, Brazil. 4 H. Kim, N. Feamster, Improving network management with software defined networking, Communications Magazine, vol. 51 (2), IEEE, 2013, pp. 114119. 5 N. McKeown, T. Anderson, H. Balakrishnan, G. Parulkar, L. Peterson, J. Rexford, Openflow enabling innovation in campus networks, ACM SIGCOMM Comput. Commun. Rev. (2008) 6974. 6 ONF, The openflow 1.3.1 specification, Tech. rep. September 6, 2012 7 Qosmos Co-publishes White Paper with Heavy Reading on The Role of DPI In An SDN World … Paris, France December 13, 2012. Network Intelligence. 8 Intel-Qosmos White Paper Service-Aware Network Architecture Based on SDN, NFV and Network Intelligence By HYPERLINK https//qosmos.com/author/qos-redacteur/ o View all articles by qos-redacteur qos-redacteur Published 02/09/2013 9 HYPERLINK https//dl.acm.org/citation.cfmid2674984 Deep packet inspection as a service Anat Bremler-Barr, Yotam Harchol, David Hay, Yaron Koral , Proceedings of the 10th ACM International on Conference on emerging Networking Experiments and Technologies, 2014. 10 Alfred V. Aho and Margaret J. Corasick. Efficient string matching An aid to bibliographic search. Commun. of the ACM, 18(6)333340, 1975. 11 Sun Wu and Udi Manber. A fast algorithm for multi-pattern searching. Technical report, Chung-Cheng University, University of Arizona, 1994. 12 Michela Becchi and Patrick Crowley. A hybrid finite automaton for practical deep packet inspection. In CoNEXT, page 1, 2007 13 Sailesh Kumar, Sarang Dharmapurikar, Fang Yu, Patrick Crowley, and Jonathan Turner. Algorithms to accelerate multiple regular expressions matching for deep packet inspection. In SIGCOMM, pages 339350, 2006. 14 Michela Becchi and Patrick Crowley. An improved algorithm to accelerate regular expression evaluation. In ANCS, pages 145154, 2007. 15 Domenico Ficara, Stefano Giordano, Gregorio Procissi, Fabio Vitucci, Gianni Antichi, and Andrea Di Pietro. An improved DFA for fast regular expression matching. Computer Communication Review, 38(5)2940, 2008. 16 Sailesh Kumar, Jonathan Turner, and John Williams. Advanced algorithms for fast and scalable deep packet inspection. In ANCS, pages 8192, 2006. 17 Fang Yu, Zhifeng Chen, Yanlei Diao, T. V. Lakshman, and Randy H. Katz. Fast and memory-efficient regular expression matching for deep packet inspection. In ANCS, pages 93102, 2006 18 Zachary K. 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In SIGCOMM, pages 2738, 2013. 24 nDPI Open-source high-speed deep packet inspection, HYPERLINK https//ieeexplore.ieee.org/xpl/mostRecentIssue.jsppunumber6895209 2014 IEEE,International Wireless Communications and Mobile Computing Conference (IWCMC).

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