Cisco recently released the latest version of our VNI Forecast, a 5-year look ahead at data traffic growth trends. I caught up with Kevin McElearney, SVP Network Engineering at Comcast, to talk about the implications this latest VNI Forecast has for Comcast’s planning. You can check out what Kevin has to say here.
In our last blog on “Advanced Flow Control” we used the metaphor of a three-dimensional collection of intersecting highways of many different kinds with a wide array of vehicles carrying various types of passengers to represent the Internet of Everything (IoE). The IoE concept has come a long way since it was first coined by the Auto-ID Center. Today the concept has broadened into a catch all for current and future network-connected endpoints, from smart meters to vending machines, security cameras, all forms of transportation, and consumer electronics ─ not to mention PCs, tablets, and smartphones. People with electronic tags will one day be connected to the IoE to monitor their health. Many dogs and cats already have chips for location tracking. The opportunity for new services will be unlimited and customers will expect instant access to networking resources to launch, alter, or eliminate those services.
Retailing has always been a tough business. But, the move to online shopping, the challenging economy and changes in shopper’s behavior has placed even more pressure on traditional retail margins. Retailers are constantly looking for ways to get more people in to their store and to spend more. Traditional retailers have long envied the massive amounts of valuable data that online retailers have available to help them better understand customer behavior and implement winning marketing tactics. Online retailers know such valuable information as: how frequently customers return, how long they spend on the site, what they looked at but didn’t buy and where they went before and after coming to the site. With this information, online retailers are able to rapidly adjust prices, promote certain items, and re-configure the layout of the site in almost real-time in order to increase the probability and value of a sale. None of these data and insights has been available to bricks-and-mortar retailers -- until now. The increasing availability of Wi-Fi in retail locations is changing all of that.
Shopping malls and retailers are increasingly offering Wi-Fi to their customers as a service to connect their mobile devices to the Internet. Hidden in this Read More »
Written By Kiran Matty, Marketing Manager, and Ola Mabadeje, Marketing Manager
If “Big Data” is crude oil, then Analytics is its refinery. According to a Cisco IBSG report, “if ‘crude” data can be extracted, refined, and piped to where it can impact decisions, its value will soar”. The trends, patterns, and insights that can be gathered from the various sources of Big Data are virtually limitless. However, this blog shall primarily focus on the analytics that can be generated by refining i.e. analyzing the data that’s resident in a mobile network and is largely untapped.
According to Cisco VNI, the number of connected devices will be three times the global population by 2017 and the global IP traffic will also increase threefold in the same time frame. Mobile Networks have not only been primed to sustain this onslaught but have also transformed into a programmable platform that can collect, correlate, and contextualize data rapidly. Network data, Policy, and Analytics interplay in a multitude of ways and form the basis of Data in Motion that’s at the heart of network monetization.
Hidden opportunities exist in the market gaps
As you might be aware, CPM (Cost per Mille) for mobile Ads is lower than that of other advertising media such as online, television, etc. This is because mobile Ads are generally untargeted, which leads to ineffective Ad campaigns, and could be attributed to a large extent to the lack of contextual awareness vis-à-vis location, demographics, browsing history, network conditions, screen size, etc. Although market researchers have perfected the measurements for other advertising media, they haven’t yet cracked the nut for mobile and the mobile metrics remain fuzzy at best which is impeding the flow of advertising dollars to mobile. On the other hand, as much as we love applications like Apple Siri and FaceTime, Angry Birds, etc., and devices like the Apple iPhone, they have turned out to be an operational nightmare in certain cases for the mobile operators around the world because of the data and signaling Tsunami that they can potentially bring about. This is due in part to lack of network analytics that can predict such surges in the network traffic with reasonable accuracy to allow for timely management of the network in terms of network capacity and bandwidth. This would eventually lead to operational efficiency and hence cost savings. Further, think about Internet of Everything and the 50 billion devices that would come online by 2020!
Mobile network operators are well positioned to address the above pain-points. With access to millions of subscribers, they can predict network and consumer behavior with high degree of accuracy quite simply because of the law of large numbers. Unlike many pure-play analytics vendors, network operators have direct access to data from a variety of sources such as CDN (Content Delivery Network), devices, applications, network billing and charging systems, not to mention the various mobile network elements. Some may even have access to subscriber Wi-Fi data. Lastly, many have the cloud infrastructure that’s needed for analyzing data at a bigger scale.
Written by Sailesh Krishnamurthy, Principal Engineer
Service providers around the world are seeing an unprecedented explosion of data in their networks. This explosion is characterized by the “Three Vs” (volume, variety and velocity) that are the typical hallmarks of challenging data problems. The service providers that embrace these problems creatively stand to unlock enormous monetization opportunities. The good news is that service providers are uniquely positioned to correlate and analyze data from across the ecosystem (client, network and cloud).
This blog post will describe some of these analytics opportunities. In my next post, I’ll discuss Cisco’s strategic plans to help service providers in this process with Cisco Prime Analytics.
The data explosion in service provider networks is extremely diverse (“Variety”) and comes from various sources including:
Mobile Data. Location, presence, devices and customers.
Video Growth. Projected to be 65% of mobile and 90% of fixed traffic by 2015.
Machine-2-Machine (M2M): 225 M2M connections by 2014— from vending machines and ATMs to connected vehicles.
Commerce. Mobile payment platforms and local offers.
Smart Networks. Capable of bandwidth optimization, content placement, SDN, and more.
Social Media. Consumer behavior, targeted advertisements.
Cloud (XaaS). All data moving to the cloud leading to more app-cloud interactions.
Unlike other players (manufacturers, content/service/app providers), service providers are Read More »