Another storage option in which the actual online storage media used in transparent to the user

Data Accessible from Anywhere

As though employees’ desire to share data is not enough of a threat to proprietary information, many business professionals want access to data from anywhere they work, on a variety of devices. To be productive, employees now request access to data and contact information on their laptops, desktops, home computers, and mobile devices. Therefore, IT departments must now provide the ability to sync data with numerous devices. And if the IT department can’t or won’t provide this capability, employees now have the power to take matters into their own hands.

Previously mentioned online storage sites can be accessed from both the home and office or anywhere there is an Internet connection. Though it might be possible to block access to some of these sites, it is not possible to block access to them all. And some can appear rather innocuous. For many, Google’s free email service Gmail is a great tool that provides a very robust service for free. What few people realize is that Gmail provides more than 7 GB of storage that can also be used to store files, not just email. The Gspace plug-in7 for the Firefox browser provides an FTP-like interface within Firefox that gives users the ability to transfer files from a computer to their Gmail accounts. This ability to easily transfer data outside the control of a company makes securing an organization’s data that much more difficult.

Examples: Long operations provide no way to cancel

Apple’s iDisk online storage service displays a phony progress bar when you copy a large file to your iDisk (Figure 7.4). The bar fills up in less than a second, then shows a barber-pole animation for 2–20 minutes, depending on the file’s size. Worst of all, the dialog box provides no time estimate and the cancel button (“X”) is disabled.

Figure 7.4.

Apple iDisk file copy: false progress bar, no time estimate, and cancel button is disabled.

At least iDisk’s dialog box has a cancel button. When MacOS converts a Postscript file to a PDF file, that can take several minutes, depending on the file’s size. During that time, it displays a phony progress dialog box with no cancel button (Figure 7.5).

Figure 7.5.

MacOS: phony progress bar with no cancel button.

Near-line

Near-line storage is the in between state between online and offline storage. Near-line systems typically do not require human intervention and data is retrieved as part of an optical storage jukebox or robotic tape system. Access times for this type of storage are typically high and can range from a few seconds to a few minutes depending on the system. The costs vary widely for near-line storage systems, but are typically half the cost of online storage options. Near-line storage is also highly scalable by adding additional tapes or optical disks to increase capacity.

What is important to Exchange 2007

For Exchange 2007, you will first need to ensure that you can provide online storage that is reliable and fast. The storage speed for Microsoft Exchange depends on the activity you perform on the server. For regular online access to email, you need to have a good I/O throughput (request rate). The size of the I/O is typically that of a database page, set to 8 KB with Exchange 2007 (with previous version of Microsoft Exchange, this was 4 KB). It may be much larger in case you can bring pages together via a single request, or if you run a backup job that does not really care about the page-level structure of the database.

For backup and recovery purposes, you need to have a good throughput (data rate). The disk throughput in 2008 can be in excess of 125 MB per second for a single disk drive (Seagate Cheetah, http://www.seagate.com/www/en-us/products/servers/cheetah/). In fact, if you optimize the disk layout, and use, for example, several disks combined in a single logical volume (RAID), you can exceed that data rate. For sequential access devices, such as tape drives, a single LTO3 tape drive can exceed a throughput of 200 MB per second in native rate. Add to that hardware compression and you can assume that those devices that sustain pretty data transmission rates for backup and recovery. Of course, they are not used on their own, and they often depend on the surrounding infrastructure and server connectivity that can have a bottleneck impact from a performance viewpoint.

Finally, we believe that it is important to make the point that the performance data explained here are based on a single component only: disk or tape drive. In reality, you will need to assemble disks together to create larger and more powerful disk units that can sustain the workload applied by hundreds of users. That is the topic of the next section.

True/False

1.

True or False? Information system hardware includes data processing and storage equipment, transmission and networking facilities, and online storage media.

True or False? Physical facility includes the buildings and other structures housing the system and network components.

True or False? Supporting facilities underscores the operation of the information system.

True or False? Personnel are humans involved in the control, maintenance, and use of the information systems.

True or False? It is possible to assess the risk of various types of natural disasters and take suitable precautions so that catastrophic loss from natural disaster is achieved.

3 Cloud computing applications

Cloud computing is a technically dense topic that has many applications in various business domains. Here is a short list to name a few:

custom relationship management

online storage management

collaboration tools

financial applications

human resources and employment services

smart homes

smart cities

Big Data

The subsequent sections describe three major applications where cloud computing is an enabling technology.

3.1 Big Data as an enabling technology for Smart homes and cities

Big data is considered the backbone technology for many applications of cloud computing in the domain of smart cities and homes. The following graph in Fig. 12.5 was produced by searching web search content trends on Google Trends for the following key words: cloud computing, big data, smart homes, and smart cities from 2014.

Figure 12.5. Google Trends Graph for Cloud Computing, Big Data, Smart Cities, and Smart Home Between 2014 and 2015

In Table 12.5, we explore the Google search index weights of cloud computing, smart homes, smart cities and big data by region.

Table 12.5. Google Trends Search Index Weight for the Key Words: Cloud Computing, Smart Homes, Smart Cities and Big Data per Region of Interest

Cloud Computing	Smart Homes	Smart Cities	Big Data
	Google search index		Google search index		Google search index		Google search index
Malaysia	19	UK	100	India	100	India	100
Australia	16	USA	41	Spain	41	Singapore	87
UK	14			UK	11	Hong Kong	69
USA	14			USA	7	Taiwan	48
Canada	11					South Korea	46
Indonesia	8					USA	44
Germany	8					Spain	38

To the reader, it is notable that Asia and North America are the two global players across all categories in addition to Germany and Spain in Europe. Although there are not too many experiences or players worldwide for smart homes or cities, this can be explained by their reliance on current advances on cloud computing and big data which we see thriving in multiple countries. We shall see major advances in smart homes and cities in the forthcoming years as the former technologies mature.

3.1.1 Big data, data fusion, and data analytics

Cloud computing and big data is a compelling combination. In a nutshell, big data refers to huge data sets in volume, data that is diverse and that include structured, semi structured and unstructured data. In today’s world, this flood of data is produced from a multitude of data sensors and gadgets such phones, RFID tags, homes, hospitals, roads, cars, public spaces, etc. This data in raw form is not easily exploitable and does not give value. In fact, what make it valuable are the insights and analytics it produces when it is analyzed. Current cloud computing systems have demonstrated large capabilities for moving data into the cloud, indexing and searching it as well as coordinating large scale cloud databases analysis. To do so, many supporting algorithms and technologies were developed and enhanced such as Map Reduce, Chord, and Dynamo. These algorithms have been adapted and optimized to serve in the cloud [9–11]. Fig. 12.6 illustrates the map-reduce algorithm in the cloud.

Figure 12.6. Big Data Map Reduce in the Cloud

In a growing number of enterprises that are requiring data analysis (Financial institutions, and scientific laboratories), Information Technology (IT) role is shifting from traditional computing grid based services to brokering cloud based big data analytics services [14] also known as Data as a Service or DaaS. Using cloud infrastructure to analyze big data makes sense for various reasons. To name a few [12]:

•

Investing in big data analysis requires large IT budget. Cloud computing provides an appealing case when it comes to resource elasticity

•

Data can come from internal as well as external sources. External data is often hosted in cloud stores so it makes perfect case to use the same infrastructure to analyze this data and keep the overall system coherent.

•

Data services such as Analytics as a Service (AaaS) are needed to extract value from big data.

Cloud computing models are thus the next logical evolution in the field of scalable analytics solutions and we start to see many start-ups operating in this field. Organization using cloud to provide AaaS can weight many factors such as security, interoperability, workload when implementing such a solution. Often, a hybrid model is used where a private cloud is used to handle and manage in-house data while a public cloud is used as an extension to further provide scalability to the system [12].

3.1.2 Trends in big data as an enabling technology

From current experiences, it is undeniable that cloud computing is a cost-effective delivery model for big data and data analytics. Cloud will enable the enterprise as well as cities to deliver a new generation of agile and innovative solutions. The first generation big data applications were based on textual data. The second or next generation of big data analytics will aggregate data from multiple sources and encodings such as voice data, video stream, car flow and transportation data, hospital data, airline data, grid energy status, homes sensors, and user and objects tracking data, among others.

3.2 Smart cities

Many of the world cities have embarked on smart city projects, including Seoul, New York, Tokyo, and Shanghai. These cities might seem like cities of a future era but with the current advances in technology and especially cloud computing, they are only exploiting to a certain extent what current technology has to offer.

3.2.1 Smart city concept

A smart city is a concept of a knowledge, digital, cyber, and ecofriendly city. Based on the specificities of each city, the following two definitions emerge:

•

“A city well performing in a forward-looking way in [economy, people, governance, mobility, environment, and living] built on the smart combination of endowments and activities of self-decisive, independent and aware citizens.” [13]

•

“A city that monitors and integrates conditions of all of its critical infrastructures including roads, bridges, tunnels, rails, subways, airports, sea-ports, communications, and water, power. Even major buildings can better optimize its resources, plan its preventive maintenance activities, and monitor security aspects while maximizing services to its citizens.” [14]

•

“A city that strategically utilizes many smart factors such as Information and Communication Technology to increase the city’s sustainable growth and strengthen city functions, while guaranteeing citizens’ happiness and wellness.” [15]

Smart cities require a lot of planning in order to create coherence between city services. This can be achieved by many models and most notably a human-centric model that is based on ICT infrastructure. Fig. 12.7 describes this model.

Figure 12.7. Cloud Computing Benefits in the Context of Smart City

The continuous evolution of the Internet and the ability to maximize user activities allowed accelerating the emergence of ideas that attempt to improve the quality of services for communities around the cities [16]. Smart cities are a new perception of what commonly provided services should be in the age of the internet. Smart cities enclose services in diverse business and technological fields such as efficient use of natural resources as electricity, water, and air quality in addition to waste management. There are many examples of smart cities around the world. Each one of these cities is revolutionizing current processes in order to improve the quality of life of their citizens while optimizing the cost of these services [15]. One of the most cheerful and bold moves by the city of Berlin is to consider cloud computing as a natural resource [17].

For smart cities services to take shape, large amounts of data emerging from many sources must be collected, analyzed and synthesized in order to take informed actions and decision automatically and semi-automatically.

3.2.2 Smarter grid

According to the energy information administration, 62% of worldwide energy generation comes from gas and coal, 13% comes from nuclear, 16% from hydraulic systems and only 4% from renewable energies [18]. There is a constant rise in energy demand to levels above 80% until 2030 and by 2040, energy demand from large economic powers such as China will double that of the USA level. Having an outage such as that of 2003 in North America creates disturbances in businesses and the economies at large. These power grid failures could in most cases be prevented if the diagnostic information was available and ready in time.

In Fig. 12.8, we illustrate the smart grid ecosystem with energy efficiency at its center. Energy is stored and distributed to users. Excess energy can be exported to third party for example. There are many challenges and opportunities in smart grids that can be addressed by cloud computing [18,19]. Examples include dynamic energy pricing and shifting potential peak demand to a different time when the price of energy is low, real time massive data streaming and analysis from sensors plugged in the infrastructure [20]. To ensure proper coordination and efficiency in this area, ultraresponsive Supervisory Control and Data Acquisition (SCADA) systems can be used. This is illustrated in Fig. 12.9. New studies suggest that new paradigms need to be devised in order to support optimized production and consumption of power as well as to estimate a wide area state of the grid.

Figure 12.8. Smart Grid Ecosystem

Figure 12.9. Cloud Enabled Big Data Analytics

3.3 Smart home

3.3.1 Concept

The idea of moving home automation to cloud infrastructure is to provide a simple deployment model for client when deciding to install home automation devices [23]. From usability point of view, any new installation shall be easy to use, vendor agnostic as well as interoperable between devices providing the same or complementary data. IBM in [23] has defined three major characteristics of new smart home appliances:

•

Instrumented: having the ability to sense and monitor changing conditions.

•

Interconnected: having the ability to interact with people, systems and other objects.

•

Intelligent: having the ability to make decision on data and produce a better outcome.

A smart home defines and offers many new capabilities. Here are few examples to name a few:

•

entertainment and smart TVs

•

energy management

•

safety and security

•

health and convenience

•

user recognition and home profile management

•

automatic contact of emergency services

•

automatic virtual shopping

•

practical data display

Cloud computing provides and intelligent platform to connect interoperating services [23].

As illustrated in Fig. 12.10, smart homes will be equipped with a variety of sensors such as power meters and monitoring devices. These devices will communicate together and contact services running in the cloud to provide the desired functionality. Table 12.6 illustrates how home devices will become smarter [23].

Figure 12.10. A Connected Smart Home

Table 12.6. Example of Smart Devices

Home Device	Description in a Smart Home Context
Home energy distributer	On the basis of the activities in the home and the surrounding building, energy usage by other home appliances will be adaptive to optimize the cost of the KWH as well as the load of the grid. This adaptive information is extracted through continuous sensor data collection from the home as well as continuous behavior analysis and comparison with other relevant data from the cloud
TV set	Propose programs and content on the basis of user watch list history Propose targeted ads on the basis of content
Refrigerator	Adjust the thermostat on the basis of the volume of the food items it contains
Washer and dryer	Determine the water temperature in the wash/rinse/dry cycle on the basis of the load volume, dirt level, etc.
Water heater	Water heater that turns on to heat the water when the cost of energy is cheap and let the water cool off when this water is not needed
Air conditioner	It will consume and match usage and climate patterns, power cost and grid state in order to provide the most optimal temperature in the home at an optimal cost

3.3.2 Smart homes enabled by the cloud

Cloud computing platform offering or PaaS is ideal for providing the basic layer behind home automation. It allows dynamic allocation of resource applications. Provided the standardized web service interfaces, it is possible to enable dynamic composition of solutions in a plug and play mode. Relying on the cloud, smart home solution vendors can easily scale their solutions to millions of users worldwide. It is because we benefit from dynamic provisioning of resources. Using common PaaS and IaaS platforms allows devices to become connected and interoperable with other devices from different vendors. This is due to the expansion of industry wide standards as well as solid consortia of market leaders. The key benefits of using cloud computing to enable smarter home can be summarized as shown below:

•

From a consumer point of view, the smart home devices are easier to use especially that the management has been moved to the cloud. This implies that no IT infrastructure needs to be put in place except a broadband network. Connecting smart home devices is only a matter of software adapters at the PaaS provider side. The extensibility of networked services along with the ability to link both existing and new devices provide reliable performance and increase service innovation.

•

From a device manufacturer point of view, relying on industry standards through cloud allows creating innovative services as well as reaching large consumer base. Open standards prevent vendors and especially start-ups from being locked out of specific markets where device manufacturers have stroke specific deals. Once the cloud is the platforms, device and service manufacturers can concentrate on delivering added value business features and scale up or out in markets freely and easily.

•

From a service provider point of view, providing services on top of standardized device interface allows a shorter time to market, and better pricing due to shared IT infrastructure. Along with device manufacturer, service providers can concentrate on added value services.

3.3.3 Home cloud service delivery platform

The service delivery platform, which sits on top of cloud computing infrastructure, enables the integration and monitoring of services and composites of services. The delivery platform concept has been developed by IBM and improved with deployments in the telecom IT industry in order to provide and reach content to consumers [21].

As illustrated in Fig. 12.11, the service delivery platform is a service-oriented Architecture (SOA)-based modular component services. It provides a controlled way to add new services and by aggregating and composing these services on the cloud and simplifying the consumer based side.

Figure 12.11. Service Provider Cloud Platform

3.3.4 Emerging protocols for smart homes

In order to successfully bring cloud based smart homes to market, it is necessary to ensure proper communication between the smart home devices and the cloud. This communication relies on the following protocols and standards [21]:

•

Home gate standard: ISO/IEC 15045

•

Wired systems: USB, Ethernet, IEEE 1395

•

Low-level wireless protocols such as ZigBee, HomeRF, Wimax, Bluetooth

•

Special level interoperability such as OSGi, TAHI, and Cablehome

•

Home networking systems such as DVB, DLNA, and UPnP

•

Power line such as DS2, X10, and HomePlug

•

Specifications: HGI, ITU-T SG-5, ITU-T IPTV-GSI, and IEC TC100 gateway

10.2.2.1 Dropbox and iCloud

One of the core features of cloud computing is availability anywhere, at any time, and from any Internet-connected device. Therefore, document storage constitutes a natural application for such technology. Online storage solutions preceded cloud computing, but they never became popular. With the development of cloud technologies, online storage solutions have turned into SaaS applications and become more usable as well as more advanced and accessible.

Perhaps the most popular solution for online document storage is Dropbox, an online application that allows users to synchronize any file across any platform and any device in a seamless manner (see Figure 10.6). Dropbox provides users with a free amount of storage that is accessible through the abstraction of a folder. Users can either access their Dropbox folder through a browser or by downloading and installing a Dropbox client, which provides access to the online storage by means of a special folder. All the modifications into this folder are silently synched so that changes are notified to all the local instances of the Dropbox folder across all the devices. The key advantage of Dropbox is its availability on different platforms (Windows, Mac, Linux, and mobile) and the capability to work seamlessly and transparently across all of them.

Another interesting application in this area is iCloud, a cloud-based document-sharing application provided by Apple to synchronize iOS-based devices in a completely transparent manner. Unlike Dropbox, which provides synchronization through the abstraction of a local folder, iCloud has been designed to be completely transparent once it has been set up. Documents, photos, and videos are automatically synched as changes are made, without any explicit operation. This allows the system to efficiently automate common operations without any human intervention: taking a picture with your iPhone and having it automatically available in iPhoto on your Mac at home; editing a document on the iMac at home and having the changes updated in your iPad. Unfortunately, this capability is limited to iOS devices, and currently there are no plans to provide iCloud with a Web-based interface that would make user content accessible from even unsupported platforms.

There are other solutions for online document sharing, such as Windows Live, Amazon Cloud Drive, and CloudMe, that are popular and that we did not cover. These solutions offer more or less the same capabilities of those we’ve discussed, with different levels of integration between platform and devices.

Online storage

To protect data, you need to control where it resides. If you store data in the Cloud, there’s an added measure of complexity. Cloud storage (also often referred to as online storage) is a service that allows you to store data on a server belonging to a third party and accessed over the Internet. You might use a service to back up the contents of your phone, tablet, or computer, or use it to store and share important documents, photos, music, or other files. Some Cloud services also provide syncing, so that you can offload files and settings from your computer to servers, making them accessible between other computers you log into. Some popular cloud storage solutions include:

iCloud (www.icloud.com)

OneDrive (http://onedrive.live.com)

Dropbox (www.dropbox.com)

Depending on the service and whether it supports synchronizing between devices, your data may exist in different locations. For example, a file might only be stored on an Internet server, or a copy may be on your computer and an Internet server. When using OneDrive, your files are stored online, but a copy of the file also resides on your computer. If you modify a document or file on your computer, the updated file is uploaded to the Cloud, so that the same version now resides on both file systems. If you’re not connected to the Internet, the next time you go online, OneDrive will sync the files and update the online version with an updated one on your computer.

While a Cloud storage service should encrypt data as its transmitted and stored, and have security measures in place to protect it from attack or disasters, this isn’t always the case. There are many providers, and not all of them are equal. While every provider will claim your data is secure and their business is stable, an unreliable or unstable company may lack the resources or experience to live up to their promises. If the company goes bankrupt or has a disaster, your data could be lost.

You should also be aware that as data is stored in different locations, it increases the surface area for possible attacks. Not only could data be recovered from the computers and devices used to access files in Cloud storage, a hacker or malware could potentially access the data as it moves over multiple networks, and is replicated across different servers in a data center. Even though you see your data on the Cloud, you wouldn’t know if it’s been replicated to hard disks or servers that are being disposed, at risk of unauthorized access, or viewed by people within the company who have been compromised or corrupt.

If you’re unsure of your settings or how Cloud storage works, you might even be surprised that your files are being backed up or synced to the Cloud. When Microsoft added OneDrive (then called SkyDrive) it automatically synced the PC and Internet server. Similarly, in checking the default settings on your phone, or settings for certain security apps, you may find that it’s automatically set to sync and backup files to a Cloud service. To control what’s sent to the Cloud, you should check the settings on your computer and devices, and any apps that may provide online storage. For example:

On an iOS device, such as an iPhone or iPad, you would tap Settings, tap iCloud, and then tap on the iCloud features you don’t want to use so they appear disabled. These include iCloud Drive, Photos, Mail, and Contacts.

On a Mac, you would click the Apple menu, click System Preferences, click iCloud, and then deselect features you don’t want to use.

If you use iCloud on a Windows machine, you would open the iCloud for Windows program, and then deselect features you don’t want.

You should also determine how the service provider handles deleted files. Rather than erasing a deleted file, it may be hidden or reside in a Trash or Recycle Bin. For example, in DropBox, you can click on a trash-shaped icon to view deleted files. To permanently delete them, you need to right-click on a deleted file that appears in gray, and then click Permanently delete from the menu that appears.

Persistent Interface Index Assignment

It is possible that the device preserves its assignment of ifIndexes in a persistent manner. That is, the device remembers which interfaces were assigned which ifIndex values by storing that information in some form of nonvolatile online or offline storage. The advantage of this approach is that any network management system that is monitoring this device need not reread the entire ifTable to relearn the ifIndex assignments in the event that the device reboots. This feature may be rather important if the NMS has a requirement that limits the amount of time the NMS may take to reread the ifTable and reinitialize itself accordingly. The NMS itself may have limitations on having to reset the ifTable if a device reboots, due to its internal bookkeeping of a device's interface objects. Due to the overhead involved in implementing persistent ifIndex assignment, the maintenance of Interface Indexes in a persistent manner is optional. Therefore, we recommend that operators and network managers interested in this feature consult with their device vendors about this functionality well in advance. This is especially important in the event that this feature must be implemented from scratch.

When an agent reboots, it may choose to remember the last ifIndex value and begin assignment from that point on, or it may begin assignment from one. When interfaces are deleted due to being disassociated within software or are physically removed, their ifIndexes may be reused by the agent. However, these values should not be reused for “a long time” so as to not confuse any NMS. That is, the value should not be reused for as long a time as an NMS might have been monitoring the interface and not received either a notification indicating the removal of the interface or a polling cycle that revealed that its RowStatus was destroyed. Due to the size of the ifIndex space (Unsigned32), typical systems will not reuse an ifIndex for hours, days, or until they are rebooted. If a system maintains indexes persistently, it may take many thousands of system reboots before it will reuse an ifIndex.

Device types

The primary concern in selecting device types is whether you want to save money on storage costs. Define whether you want the archive stored on the front line, in always accessible storage, in low-cost semi-online storage, or in even lower-cost offline storage.

Some common types of storage are tape, write-once/read-multiple (WORM) devices, SAN devices, network-attached disk storage, or normal computer-attached disk storage. Of course tape is very cheap, but recovery of data takes a long time and accessibility can be a real problem. Searching data is mostly impractical. Tape also has a shorter life span, requiring copying to new tape media at frequent intervals. WORM devices appear to have an update prevention advantage. Although this is true, it prevents selective discard of data, requiring disposing of the entire media to accomplish discard. As such it is generally not appropriate for database archiving, since there are other ways of achieving protection from updates while putting the archive on updatable devices.

SAN devices seem to offer the best place to host a database archive. They have large capacity, are accessible online (although slow), have longer media life spans, and are lower cost. However, acquiring a SAN and developing the expertise to manage the devices can be an obstacle. Most IT departments are already using SAN devices, thus making them a logical choice.

Computer-attached storage is the most accessible but also the most expensive option. In addition to cost, managing the storage in an operational setting will make life more difficult for the storage administrators.