During the past few years, the deployment of cloud architectures has accelerated to support various consumer and enterprise applications such as email, word processing, enterprise resource planning, customer relationship management and the like. Traditionally, co-located servers, storage and networking moved to the cloud en masse in the form of a service, with overlying applications that have been and remain very insensitive to delay and jitter.
But the fast-emerging next generation of business applications require much tighter service level agreements (SLA) from cloud providers. Applications such as Internet of Things, smart grids, immersive communications, hosted clients and gaming are some good examples. These use cases tend to be marked by periods of high interactivity, so delay and jitter for the network, computer and storage must be minimized. During times of normal interactivity, the applications are in steady-state condition, requiring minimal SLAs from the infrastructure resources.
Emerging use cases drive demand for two-tier cloud architectures
These emerging use cases are driving the rise of two-tier cloud architectures. The key for these architectures to succeed is efficiency: they must be cost-effective to deploy and guarantee a tight SLA for applications while leaving the rest of the carrier and cloud infrastructure unchanged. What’s more, the application service needs to move closer to the end user, but only for the duration of the real-time interaction. These measures help ensure that the customer’s application-specific requirements for delay and jitter are met without requiring major upgrades to the carrier or cloud infrastructures.
In this two-tier cloud architecture, the first cloud tier, also referred to in the industry as centralized cloud, is where the applications typically reside. The second cloud tier is invoked on demand, and the application’s virtual machine along with its relevant network, application and storage data shift to this tier. Keep in mind that the second tier can be instantiated as part of an existing service provider network element or as a stand-alone infrastructure element closer to the end user.
A connected patient heart monitor provides a useful example. During most of its operational time, the device may be collecting data only periodically, and with no need for any interactions with medical staff. But when the heart monitor detects an abnormality, the application hosted in the cloud must instantly be moved closer to the user in order to provide interactivity. For this use case, the second tier cloud must host the application, assess the patient’s condition, retrieve relevant historical information and alert the medical staff for a possible medical response.
The key, then, is to move applications from tier one to tier two clouds seamlessly. LSI® Axxia® multi-core communication processors feature an architectural scalability for network acceleration and computer cluster capabilities that provide this seamless bridge between the two clouds. In order for the two-tier cloud architectures to thrive, they need three fundamental elements:
a. On-demand resource provisioning
Many cloud datacenters are squarely focused on deploying end-to-end resource provisioning tools to improve efficiency. Not the least among these is the fast-growing end-to-end orchestration ecosystem for OpenStack® software, though there are many proprietary solutions. End-to-end orchestration tools need to be aware of all the second-tier cloud datacenter components. In some cases, OpenStack is even being deployed to boot up second tier cloud components. However, a big challenge remains – maintaining a steady state and full capabilities of various distributed second-tier cloud components.
b. Efficient virtual machine movements
For tiered cloud architectures to thrive, they must also transfer enough network, application and storage data to sustain continuing operations of the application at the second tier. However, many of today’s virtual machine migration solutions are not geared to moving datacenter resources efficiently. In a two-tier cloud architecture, the virtual machine migration may traverse many hops of carrier infrastructure, increasing total cost of ownership (TCO). In addition, complete virtual machine images must be transferred before the destination station can start the machines, extending the time it takes for the second tier to take control. The upshot is that optimized solutions need to be developed to enable seamless virtual machine migrations.
c. Network and storage acceleration of resource-constrained tier-two clouds
Unlike the first cloud tier, the second cloud tier is bound to be resource-constrained, requiring significant data acceleration for both the networking and storage layers. A 16-core full SMP ARM®-based processor like the LSI Axxia 5500 processor, with its processor cores and, more importantly, its fully programmable acceleration engines for offloading security, deep packet inspection, traffic management and other functions is well-suited for network acceleration of the second cloud tier. Keep in mind that specific acceleration needs vary based on the location of the second tier cloud. For example, the acceleration requirements of the second cloud tier would differ depending on whether it is part of a service provider access aggregation router or located on a remote lamp post. The need for security acceleration, in particular, increases tremendously in cases where data associated with particular data events must be authenticated before further processing. To support these various acceleration needs, the second cloud tier can be built out of fairly homogeneous and scalable ARM-based hardware components with differing acceleration builds tuned to specific tasks running on it.
Momentum for greater connectivity builds
Momentum behind billions of connected things/machines across industrial and consumer applications to create a more connected, interactive world is building. Two-tier clouds and other innovative architectures are emerging at an accelerated pace to meet demand for this higher order of connectivity. And it is solutions like the LSI Axxia processor that promise to enable the scalable, flexible acceleration required for these emerging two-cloud architectures.
Tags: ARM, Axxia multi-core communications processor, cloud datacenter, enterprise applications, immersive communications, Internet of Things, network acceleration, Networking, servers, smart grids, Storage, storage acceleration, two-tier cloud architectures, virtual machines
The staggering growth of smart phones, tablets and other mobile devices is sending a massive flood of data through today’s mobile networks. Compared to just a few years ago, we are all producing and consuming far more videos, photos, multimedia and other digital content, and spending more time in immersive and interactive applications such as video and other games – all from handheld devices.
Think of mobile, and you think remote – using a handheld when you’re out and about. But according to the Cisco® VNI Mobile Forecast 2013, while 75% of all videos today are viewed on mobile devices by 2017, 46% of mobile video will be consumed indoors (at home, at the office, at the mall and elsewhere). With the widespread implementation of IEEE® 802.11 WiFi on mobile devices, much of that indoor video traffic will be routed through fixed broadband pipes.
Unlike residential indoor solutions, enterprise and public area access infrastructures – for outdoor connections – are much more diverse and complicated. For example, the current access layer architectures include Layer 2/3 wiring closet switches and WiFi access points, as shown below. Mobile service providers are currently seeking architectures that enable them to take advantage of both indoor enterprise and public area access infrastructure. These architectures must integrate seamlessly with existing mobile infrastructures and require no investment in additional access equipment by service providers in order for them to provide a consistent, quality experience for end users indoors and outdoors. For their part, mobile service providers must:
The following figure shows the three possible paths mobile service providers wanting to offer indoor enterprise/public can take. Approach 1 is ideal for enterprises trying to improve coverage in particular areas of a corporate campus. Approaches 2 and 3 not only provide uniform coverage across the campus but also support differentiating capabilities such as the allocation of application and mobility-centric radio spectrum across WiFi and cellular frequencies. A key factor to consider when evaluating these approaches is the extent to which equipment ownership is split between the enterprise and the mobile service provider. Approaches 2 & 3 increase capital expenditures for the operator because of the radio heads and small cells that need to be deployed across the enterprise or public campus. At AIS, LSI is demonstrating approach 2.
The last but certainly not least important consideration between approaches 2 and 3 is whether these indoor/outdoor small cells employ self-organizing network (SON) techniques. For service providers, the small cells ideally would be self-organizing and the macro cells serve any additional management functions. The advantage of approach 3 is that it offloads more of the macro cell traffic and makes various campus small cells self-organizing, significantly reducing operational costs for the service provider.
The United Nations finding that mobile broadband subscriptions are surging in developing countries, reported by The New York Times on Sept. 26, is no surprise. Equally unsurprising, the growing number of users, density of users and increasing bandwidth needs of applications likely are continuing to strain existing wireless networks and per-user bandwidths not only in developing countries but worldwide.
But rising pressure on bandwidth, coupled with increasingly data-intensive applications, isn’t the whole story. Minimizing end-to-end latency – from user to network base station and back again – is crucial in enabling banking, e-commerce, enterprise and other important business applications. Why? The greater the latency, the more likely visitors are to lose interest if the responsiveness of the website is sluggish. A connection may have plenty of throughput over a period of time, but response time determines the user experience.
The bandwidth-per-user and end-to-end network latency constraints are bound to drive changes both to the front haul and backhaul access networks. LTE and WiFi seem to be clear winners for the front haul network (replacing wired LAN technologies). On the backhaul, given the capacity needs, wired and wireless networks are bound to converge but will likely offer many options that will continue to co-exist like LTE, Fiber, Cable, xDSL and Microwave.
For our part, LSI has deep experience building mission-critical networks for service providers and datacenters – an expertise that has been brought to bear on the development of LSI® Axxia® networking solutions. These smart chips help solve the latency problem by enabling reliable, deterministic network performance to, ultimately, quicken response times and improve the user experience.
And that, after all, is just what network providers and users are after as mobile devices continue to support more applications and rising performance expectations worldwide.