Telecom White Paper Actioable Itelligece i the SDN Ecosystem: Optimizig Network Traffic through FRSA
About the Authors Sumit Kapoor Sumit is a solutio architect i the telecom busiess uit at Tata Cosultacy Services (TCS), focusig o SDN. His experiece spas across SDN applicatios ad SIP, IMS/VoIP ad CDN solutios. With a experiece of aroud seve years, Sumit has bee a key cotributor i ideatig ad implemetig SDN applicatios (solutio eablers) by leveragig SDN Cotrollers (OpeDaylight, Ope Network Operatig System) for telecom customers. Yamii Sardaa Yamii is a Techical Architect i TCS telecom busiess uit, focusig o Opestack ad virtualizatio. Her experiece spas across Opestack (Iaas) ad testig PXI/WiMAX/CDMA devices. With a experiece of over ie years, Yamii has made sigificat cotributios to developig virtualizatio solutios by leveragig Opestack ad test frameworks for telecom equipmet vedors. Shreshtha Joshi Shreshtha is also part of TCS telecom busiess uit, ad focuses o techologies such as telco cloud (virtualizatio through OpeStack ad Networkig Fuctios Virtualizatio) ad SDN (OpeDaylight, vedor specific SDN Cotrollers). She comes with two years of experiece i ideatig ad implemetig solutio accelerators for ext geeratio techologies.
Abstract Network traffic is highly dyamic these days, makig it importat for etwork maagers to maitai a agile system ad provide a high-quality user experiece. The system should also be equipped to provide a easy iterface to cotrol, moitor, ad optimize the etwork as per specific requiremets. The Software Defied Networkig (SDN) ecosystem addresses these challeges ad provides a cetralized SDN Cotroller for maagig etwork elemets. The programmable iterface of the SDN Cotrollers ca be utilized to itroduce actioable itelligece through the SDN applicatios. These applicatios gather data regardig etwork elemets, predict etwork behavior, ad trigger the SDN Cotroller through ope APIs to chage the etwork state i order to optimize the etwork performace. This paper recommeds a combiatio of a SDN Cotroller ad aalytical ode (data provider) alog with a aalytical egie or a SDN applicatio i order to add actioable itelligece to the SDN Cotroller. It also studies etwork traffic optimizatio through Flow Aware Real Time SDN Aalytics (FRSA). I this approach, the SDN applicatio aalyzes the packet data traffic, categorizes it, ad triggers the SDN Cotroller to route data through differet paths, thus optimizig the etwork traffic.
Cotets Need for Actioable Itelligece 6 Actioable Itelligece i the SDN Ecosystem 6 Desig ad Implemetatio of FRSA 8 Applicatio of FRSA to Cofigure Data Flow Paths 10 Future Work 13 Buildig a More Resiliet Network through FRSA 13
List of Abbreviatios API Applicatio Program Iterface FRSA Flow-aware Real-time SDN Aalytics JSON JavaScript Object Notatio ODL OpeDayLight POC Proof Of Cocept QoS Quality of Service REST Represetatioal State Trasfer SDN Software Defied Networkig UI User Iterface DDoS Distributed Deial of Service Attack
Need for Actioable Itelligece The volume of data that orgaizatios deal with has grow sigificatly, leadig to icreased pressure o the etwork maager to esure quality ed user experiece. Growig traffic i the etwork leads to cogestio, which i tur ca lead to iterruptio of services or eve loss of data. Oe solutio to this problem would be to icrease the badwidth ad provide more paths for data trasfer withi the etwork. But icreasig the badwidth of each etwork elemet is expesive, ad may ot be cost-effective i the log ru sice the icreased badwidth is uder-utilized whe the etwork traffic is low. The Software Defied Networkig (SDN) ecosystem offers scope to brig i itelliget moitorig ad maagemet of etwork traffic, offerig a far more efficiet ad log term solutio to this challege. SDN techology decouples etwork cotrols from the forwardig/data plae i the etworkig devices ad provides a cetralized SDN Cotroller. This eables the uderlyig etworkig ifrastructure to be abstracted for various applicatios ad etwork services. It also allows SDN Cotrollers to acquire cetral itelligece of the whole etwork, ad eables programmability, automatio ad cotrol to build flexible, dyamic, ad scalable etworks. Actioable Itelligece i the SDN Ecosystem The SDN Cotrollers' orthboud iterface provides the ability to develop applicatios usig ope APIs to measure Quality of Service (QoS), esure traffic moitorig ad maagemet, ad eable cotrol of the etwork as per user requiremets. The SDN applicatio iteracts with the data ode for real time aalytics, aalyzes the data ad processes it. It also predicts a appropriate actio ad istructs the cotroller to perform the ecessary actio i a SDN etwork. These applicatios thus become a meas to deliver 'actioable itelligece' to the etwork ad ca be cofigured to deliver services for orchestratio or security, or to eable rapid service provisioig depedig upo the kid of itelligece beig acquired ad aalyzed. For Example: Whe data is beig trasferred betwee two etwork devices, the device seds data packets to the etwork elemet to which it is coected. That etwork elemet, i tur, forwards it to other etwork elemets followig a optimal path to reach the ed device. If there is a breakage i the cable coectig two etwork elemets, the data trasfer would come to a halt. I a SDN etwork, i such a sceario, the etwork elemets have the mechaism to raise a alarm to idicate that there is a breakage i the cable ad the etwork elemets ca o loger commuicate with each other. A SDN applicatio ca gather the alarms, ad triggers the SDN Cotroller to perform a actio ad cofigure a ew virtual path for the data trasmissio, providig uiterrupted services to the user. 6
SDN Itelliget Applicatio (implemets actioable Itelligece) Network Data Aalytics Node SDN Cotroller ork Netw t e m le E ) Plae (Data ork Netw t e m Ele lae) P a t a D ( ork Netw t e m le E lae) P a t (Da Figure 1: Basic Cocept of Actioable Itelligece i a SDN system (Source: TCS Iteral) As illustrated i figure 1, the data from the etwork elemets is collected by the Network Data Aalytics Compoets, which is the forwarded to a SDN applicatio. This applicatio, i tur, processes the data ad triggers a evet for the SDN Cotroller. The Cotroller the performs the desired actio o the uderlyig etwork elemets. This cocept is utilized to update the etwork state dyamically based upo the trigger received from the SDN applicatio. Maagemet of Data Flows with Flow-aware Real-time SDN Aalytics (FRSA) I SDN, the cotrol plae drives the flow of data packets across etwork devices that reside i the data plae. Typically, as large data flows hit the etwork, there is traffic cogestio due to data packets waitig i queue to be trasmitted. We recommed the utilizatio of etwork itelligece to categorize the data flows ito small ad large flows, either accordig to the data size or the duratio for which they remai o the etwork. Based upo the data flow category, a actio ca be take to reduce the etwork cogestio by dyamically updatig the etwork flows ad providig a dedicated path for the smaller flows. For the purposes of this paper, larger flows (greater tha 125kbps) which are log persistet data (log lived flow) with admiistrator/user defied threshold time, are termed elephat flows, ad the other flows (less tha 125kbps) are termed mice flows. 7
Iitially, SDN treats both elephat ad mice flows i the same way. Irrespective of the size of the packet, the flow which comes first takes the defied path. Let's cosider a sceario where a mice flow is beig routed through the etwork ad aother flow (mice or elephat) is waitig to be trasmitted across the etwork. Sice the mice flow takes relatively less time to traverse the etwork, the waitig flow will be trasmitted soo. But if a elephat flow is beig trasmitted through the etwork, ay other flow will have to wait for a loger period of time. Flow Aware Real-time SDN Aalytics (FRSA) leverages the cocept of actioable itelligece to provide a solutio to this problem. Usig actioable itelligece, a SDN applicatio ca aalyze the data flows, categorize them ito mice ad elephat flows, ad trigger the SDN Cotroller to write the flow for the icomig traffic. This helps elimiate etwork cogestio ad loss of data. Cosider the followig scearios ad their correspodig solutios usig FRSA. Sceario 1: Mice flow is i the queue for a log time due to the trasmissio of a elephat flow. I such a sceario, the solutio is to provide oe (or more) dedicated path(s) oly for mice flows ad leave other paths for elephat flows. Wheever a elephat flow is ecoutered, the SDN applicatio triggers the cotroller with the flow iformatio to sed the data o the alterate path for the elephat flow, thus freeig the dedicated path for the mice flow. Sceario 2: Multiple elephat flows are beig trasmitted over the etwork. I this case, multiple paths are cofigured with assiged priorities for elephat flows. Wheever a elephat flow is ecoutered, it is set over the highest priority path available for elephat flows. I case of multiple elephat flows, they are set over differet elephat paths o a first come, first served basis. Desig ad Implemetatio of FRSA To implemet FRSA i a SDN etwork, a SDN applicatio eeds to be programmed to meet the specific objectives of the etwork. A proof-of-cocept (PoC) SDN applicatio was desiged to demostrate the implemetatio of FRSA i this paper. Its compoets, architecture ad the ivolved APIs have bee explaied here. A SDN applicatio for FRSA eeds to have the followig compoets: 1. A aget o the etwork elemet to gather iformatio o the data flows, ad sed it to the collector. 2. A collector to determie the kid of flow (elephat or mice) based o the iformatio provided by the aget. It categorizes the flows depedig upo the duratio ad size of the iformatio to be trasmitted. It the triggers a evet ad seds the iformatio i JSON format to the SDN applicatio. 3. A SDN applicatio that idetifies the shortest available path for the flow ad eables the SDN Cotroller OpeDayLight (ODL) to write the required flows o the switch usig the REST APIs. 8
The SDN applicatio uses the followig compoet APIs to iteract with the ODL cotroller. Topology Maager API that provides iformatio o the idividual odes ad the way they are coected to each other. Flow Programmer API that maages read/write flows o the switches. Statistical Flow Maager API that provides iformatio about the curret path beig used by the flow. 4. SDN Cotroller to write the flows o the uderlyig switches. The applicatio uses the cotroller's Northboud APIs to write the flows ito the etwork. Figure 2 illustrates the architecture of the SDN applicatio. FRSA User Iterface Chage Request Service Maager ALTO Re st Ca ll R eq ue st Flow Modifier SDN Cotroller Rest Call Request Sflow-RT (Traffic Aalyzer) FTP Trasfer Flow Idetifier Re st t es u eq Ca ll R ll R eq ue t es st Sflow-RT : Makes the rest call request for every ode of the topology to aalyze the traffic ODL : Cotrol to write, reads ad fetches flow details. Flow Idetifier : Idetifies the elephat flow. Flow Modifier : Modifies the flow as per the elephat/mice coditio. ALTO : Detects the shortest path betwee hosts based o Quality Of Service Service maager : Seds various requests to the UI. Ca R Miiet Topology (10 switches S1-S10 ad four hosts H1-H4) Figure 2: Architecture of FRSA implemetatio (Source: TCS Iteral) I this illustratio, the aget used is sflow-rt Aget, collector is sflow-rt collector, SDN Cotroller is OpeDayLight (ODL) ad the applicatio is FRSA SDN-App. Miiet Topology, 9
as show i Figure 3 with 10 switches S1 S10 ad 4 Hosts H1 H4, has bee used as the uderlyig etwork. Figure 3: Miiet topology structure (Source: TCS Iteral) Applicatio of FRSA to Cofigure Data Flow Paths We ow look at how FRSA ca be applied to cofigure optimized data paths i the case of the followig four scearios: Sceario 1: Flow 1 Mice (h1 -> h3); Flow 2 Mice (h2 -> h4) Sceario 2: Flow 1 Elephat (h1 -> h3); Flow 2 Mice (h2 -> h4) Sceario 3: Flow 1 Elephat (h1 -> h3); Flow 2 Elephat (h2 -> h4) Sceario 4: Flow 1 Mice (h1 -> h3); Flow 2 Elephat (h2 -> h4) I the FRSA implemetatio desiged for this study, the followig three paths have bee programmed o the etwork elemets: Path-M - through switch 2 (Switch1 -> Switch2 -> Switch3 -> Switch4): The oly dedicated path for mice flows.¹ Path-E1- through switch 8 (Switch1 -> Switch8 -> Switch9 -> Switch 10 -> Switch4): The highest priority path for elephat flows. This path is chose wheever a elephat is ecoutered, ad o other elephat is curretly flowig through the etwork. Path-E2 - through switch 5 (Switch1 -> Switch5 -> Switch2 -> Switch6 -> Switch7 -> Switch4): The secod highest priority path for elephat flows. This path is chose wheever a elephat is ecoutered ad aother elephat is already flowig through the path-e1. [1] Depedig upo the badwidth available, oe or more dedicated paths for mice/elephat flows ca be cofigured. I the cotext of this paper, there is oly 1 dedicated path for mice flow ad 2 paths for elephat flows. 10
The four defied scearios ca be hadled by FRSA i the followig maer to cater to the occurrece of elephat ad mice flows i the etwork: Sceario 1: Mice (h1 to h3), Mice (h2 to h4): I figure 4, a mice flow (marked gree) is flowig from h1 to h3 through Path-M, ad aother mice flow (marked red) is waitig to be set from h2 to h4. As there is oly oe path for mice flows (through Switch1 -> Switch2 -> Switch3 -> Switch4), the secod mice flow waits for the first oe to traverse the path, ad both go through the same path (Path-M), oe after the other. The throughput graph also shows that the mice data is trasmitted oe after the other. Figure 4: Sceario 1 Sceario 2: Elephat (h1 to h3), Mice (h2 to h4): I figure 5, a elephat flow (marked gree) is flowig from h1 to h3, ad a mice flow is beig set from h2 to h4. Sice there is oly oe elephat flow, it flows through the highest priority elephat path (Path-E1 show i gree). The mice flow does ot wait for the elephat flow ad is trasmitted through the dedicated mice path (Path-M show i red). As show i the throughput graph, the mice flow traverses Path-M ad the elephat flow starts movig through the etwork usig Path E1. Therefore, o trasmissio is affected ad both elephat ad mice flows are routed simultaeously. Figure 5: Sceario 2 11
Sceario 3: Elephat (h1 to h3), Elephat (h2 to h4): Figure 6 shows a elephat flow traversig from h1 to h3 (marked gree), ad aother elephat, which is beig set from h2 to h4 (marked red). The elephat flow that is ecoutered first moves through the highest priority elephat path (Path-E1 show i gree). As soo as the secod elephat flow appears, it traverses through the secod elephat path available (Path-E2 show i red). As show i the throughput graph, both elephat flows traverse simultaeously through their respective paths. Figure 6: Sceario 3 Sceario 4: Mice (h1 to h3), Elephat (h2 to h4): I figure 7, a mice flow is beig routed from h1 to h3, ad a elephat is waitig to be set from h2 to h4. The mice flow traverses through the dedicated mice path (PathM show i gree). The elephat flow does ot have to wait for the mice flow ad flows through the highest priority elephat path (Path-E1 show i red). As show i the throughput graph, two elephat flows are traversig through their idividual paths. Whe oe of the elephat flows (marked gree) is coverted ito a mice flow, its path chages ad it is set through Path M. The other elephat flow (marked red) keeps movig through path E1. Figure 7: Sceario 4 12
Future Work Curretly flows are characterized o the basis of data size. FRSA ca be exteded to hadle a sceario where data is characterized based o size ad time. Followig are the four categories of traffic flow o this basis: Log Persistet Large Data: For example, Hadoop applicatios data Log Persistet Short Data: For example, video streamig Short Persistet Short Data: For example, pictures or video clips Short Persistet Large Data: For example, search applicatios The sflow-rt ca moitor the lik for the type of data ad trigger a evet to the SDN app. The SDN app ca the decide the paths for these differet data types of data ad trigger the cotroller to cofigure the switches accordigly. Buildig a More Resiliet Network through FRSA FRSA, used for etwork traffic optimizatio, is oe of the use cases for actioable itelligece i the SDN ecosystem. It addresses the issue of etwork cogestio ad loss of data due to varied etwork traffic. Actioable itelligece ca be utilized i various other ways to cater to the diverse eeds of the evolvig etwork ecosystem. It is a promisig approach for etwork maagers to dyamically cofigure, cotrol, ad optimize the etwork ad offers beefits such as better QoS ad etwork moitorig. Also, it ca be used for detectio of behavioral security threats such as Distributed Deial of Service (DDoS) attacks as it treats log lived large flows separately from other flows. 13
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