As the workforce becomes wireless so does the ... - Connect-World

Smoothing Mobile mobile payment broadband Mobile systemsaccess peaksthe network is to invest in upgrading to faster(higher bandwidth) backhaul connections.The viable options tend to fall into threemajor categories:• Add capacity to the existing backhaulnetwork - this is often the quickest andeasiest to accomplish operationally.However, it can also be the mostexpensive as it does not fundamentallychange the economics. An example ofthis approach is to add additional T1/EIleased lines or TDM microwave capacityto a cell site.• Upgrade to packet-based backhaul - thisapproach requires significant planning,time, and capital investment. However,it can provide a significant leap incapacity while lowering the recurringoperational cost per Mbps of incrementalbandwidth. Examples of this approachinclude upgrading from T1/E1 coppercircuits to fiber fed, Carrier Ethernetservices or upgrading from TDM-basedmicrowave to Packet/Ethernet-basedmicrowave. Both of these approachesrequire major network, equipment, rightof-wayagreements, spectrum leasing,and operational upgrades that can incursignificant time and cost.• Offload and divert certain backhaultraffic - this approach offloads mobiledata traffic to lower cost transmissionalternatives. Examples of this approachinclude xDSL offload at the basestation and the use of femtocells andWi-Fi hotspots that can divert the dataoff the macro network onto cheaperfixed broadband connections. Theseapproaches can be effective but haveeconomic, operational, spectrumplanning, policy and SLA implications.While these options can be effective in anumber of cases, they are typically expensive,reactive, and do not fundamentally solve theunderlying challenges: exponential growthof mobile data services; the cost and time todeploy new transport; and the unpredictablenature of when and where congestion will occur.The operational impact of high demandmobile broadband peaksIn the course of conducting traffic studieswith a variety of network operators aroundthe world, Sycamore has accumulated a rangeof interesting data that sheds light on theevolving characteristics of mobile broadbandtraffic and the underlying impact of differentcontent types (mix) and usage patterns. Typicalcontent types include video, images, text, andother binary data that are transported through avariety of protocols between users and servers.The increase in smartphone usage has driven adramatic increase in the number of data sessionsin mobile networks, with greater than ten timesthe normal number of session attempts relativeto voice-only handsets.While these trends have clearly increasedbaseline traffic, what is often overlooked is thenetwork impact of high demand traffic peaks,which have increased significantly. Most ofthe congestion issues in the RAN, in fact, tendto be short-term or transitory, such as spikesin traffic demand during peak hour periods orunpredictable bandwidth surges caused by flashevents. High demand consumption peaks caneasily be four to five times the baseline traffic,and are most frequently driven by applicationssuch as Internet video and bandwidth-intensivedownloads of software updates.It becomes cost prohibitive, not to mentionproblematic, for a mobile operator to size theirnetwork (i.e., add capacity) to accommodatethis type of peak traffic since it is not easy topredict where or when those peaks will occur.And while operators will continue to utilizebandwidth expansion options to address pointsof congestion in their network, this alone won’tsolve the quality of service issues that highdemand consumption peaks cause. For thesereasons there is growing interest in technologiesthat enable operators to reduce the traffic loadstraversing the backhaul and adapt in real-time -like a shock absorber - to the dynamics of peaktraffic bursts.Targeting RAN congestion with adaptivecontent optimizationAdaptive content optimization representsa different approach to helping operatorsmanage the growth of mobile broadbandtraffic and its attendant operational expense inthe cost-sensitive RAN. Unlike mobile corebasedoptimization schemes and proxy webcaches, which primarily address upstream andinterconnection bandwidth to the Internet,adaptive content optimization can dramaticallylower capacity requirements specificallybetween the Node B and RNC. In this part ofthe network, even modest bandwidth (cost)savings can have a disproportionately positiveimpact on profitability.Adaptive content optimization reducesthe traffic volume traversing the RAN byexamining user content flows (including alltraffic types - video, images, text, P2P) andapplying advanced lossless data optimizationtechniques and adaptive learning algorithmsin real time. This approach aims to reducepeak bandwidth requirements in the backhaulnetwork and improve subscribers’ quality ofexperience, providing operators with a way tore-balance their service delivery economics inline with revenue growth - not traffic growth.Adaptive content optimization also providesoperators with three important ways tooptimize current network investments whileeasing the transition to the next generationof infrastructure. First, it addresses the maindrivers of mobile broadband: IP video andInternet content - including P2P. Second, it isarchitected for all-IP HSPA radio networks, so itis a natural fit with LTE. Third, the technologyis scalable to support LTE as a network overlay(the way most HSPA operators will deployLTE), so existing HSPA sites can be efficientlycombined with LTE radio deployments as theyare rolled out.ConclusionMobile operators across the globe areexperiencing unprecedented uptake formobile broadband services but strugglingwith the resulting network congestion andincreasing costs that come with this success.For US mobile operators in particular, giventhe large populations they must serve andbroad geographies their networks must cover,the challenge will be to continue upgradingtheir networks while delivering a good userexperience and managing service delivery costsper MB in line with revenue growth rather thantraffic growth. Adaptive content optimizationis a compelling way to help operators relievetraffic congestion and thereby improve the userexperience, delay infrastructure growth, andimprove their service delivery economics. •North America 2010 • 35