Home > Store

Mesh-based Survivable Transport Networks: Options and Strategies for Optical, MPLS, SONET and ATM Networking

Register your product to gain access to bonus material or receive a coupon.

Mesh-based Survivable Transport Networks: Options and Strategies for Optical, MPLS, SONET and ATM Networking


  • Sorry, this book is no longer in print.
Not for Sale


  • Copyright 2004
  • Dimensions: 7x9 1/4
  • Pages: 880
  • Edition: 1st
  • Book
  • ISBN-10: 0-13-494576-X
  • ISBN-13: 978-0-13-494576-7

Next-generation architectures for survivable networks.

"Always on" information networks must automatically reroute around virtually any problem-but conventional, redundant ring architectures are too inefficient and inflexible. The solution: mesh-based networks that will be just as survivable-and far more flexible and cost-effective. Drawing heavily on the latest research, Wayne D. Grover introduces radical new concepts essential for deploying mesh-based networks. Grover offers "how-to" guidance on everything from logical design to operational strategy and evolution planning-including unprecedented insight into migration from ring topologies and the important new concept of p-cycles.

  • Mesh survivability: realities and common misunderstandings
  • Basic span- and path-restoration concepts and techniques
  • Logical design: modularity, non-linear cost structures, express-route optimization, and dual-failure considerations
  • Operational aspects of real-time restoration and self-organizing pre-planning against failures
  • The "transport-stabilized Internet": self-organizing reactions to failure and unforeseen demand patterns
  • Leveraging controlled oversubscription of capacity upon restoration in IP networks
  • "Forcers": a new way to analyze the capacity structure of mesh-restorable networks
  • New techniques for evolving facility-route structures in mesh-restorable networks
  • p-Cycles: combining the simplicity and switching speed of ring networks with the efficiency of mesh networks
  • Novel Working Capacity Envelope concept for simplified dynamic demand provisioning
  • Dual-failure restorability and the availability of mesh networks

This is the definitive guide to mesh-based networking for every system engineer, network planner, product manager, researcher and graduate student in optical networking.

Extensive Web-based Appendices and Supplements

Contains new resources for designing and analyzing mesh-based survivable networks, including AMPL models, software, course notes, presentations, network libraries, student problems and suggested research projects.

Sample Content

Online Sample Chapter

Fiber Cable Failure Impacts, Survivability Principles, and Measures of Survivability

Downloadable Sample Chapter

Download the Sample Chapter related to this title.

Table of Contents

About the Book's Web Site www.ee.ualberta.ca/~grover/




Introduction and Outline.


1. Orientation to Transport Networks and Technology.

Aggregation of Service Layer Traffic into Transport Demands. Concept of Logical versus Physical Networks: Virtual Topology. Multiplexing and Switching. Concept of Transparency. Layering and Partitioning. Plesiochronous Digital Hierarchy (PDH). SONET / SDH. SONET Overheads. Generic SONET Terminal Multiplexer. Generic SONET Add/Drop Multiplexer. Digital Cross-Connect Systems. Hubs, Grooming and Backhaul. Fundamental Efficiency of Edge Grooming and Core Transport. Broadband ISDN and Asynchronous Transfer Mode (ATM). Concept of Label-Switching: The Basis of ATM and MPLS. Multi-Protocol Label Switching (MPLS). Network Planning Aspects of Transport Networks. Modularity and Economy-of-Scale. Fiber Route Structures. Network Redundancy. Shared-Risk Entities and Fault Multiplication. Demand Patterns. Short and Long-Term Transport Network Planning Contexts.

2. Internet Protocol and Optical Networking.

Increasing Network Efficiency. DWDM and Optical Networking. Coarse and Dense WDM. Optical Amplifiers. Regenerators. Optical Add/drop Multiplexers (OADMs). Transparent, Opaque and Translucent Optical Networks. Routing and Wavelength Assignment (RWA) Problem. Optical Cross-Connects (OXC). Wavelength Path Optical Cross-connect (WP-OXC). Optical Cross-Connect for Virtual Wavelength Paths (VWP-OXC). Partial Wavelength Converting OXC (PVWP-OXC). Data-Centric Payloads and Formats for the Transport Network. Computer Interconnect and SAN. Gigabit Ethernet (GbE) and 10 Gb/s Ethernet (10GbE). Enhancing SONET for Data Transport. Generalized Framing Procedure (GFP). Virtual Concatenation (VC). Link Capacity Adjustment Scheme (LCAS). Optical Service Channels and Digital Wrapper. Optical Service Channel (OSC). Digital Wrapper. IP-Centric Control of Optical Networks. Basic Internet Protocols. TCP. OSPF. Multi-Protocol Label Switching (MPLS). Extensions for IP-Centric Control of Optical Networks. OSPF-TE. Link Management Protocol (LMP). MPlS and Generalized MPLS (GMPLS). Constraint-Based Routing Label Distribution Protocol (CR-LDP). Network Planning Issues. Does IP-Centric Control Also Imply an “All-router” Network? Concept of a “Transport Stabilized” Internet.

3. Failure Impacts, Survivability Principles, and Measures of Survivability.

Transport Network Failures and Their Impacts. Causes of Failure. Crawford's Study. Effects of Outage Duration. Is 50 ms Restoration Necessary? Survivability Principles from the Ground Up. Physical Layer Survivability Measures. Physical Protection Methods. Reducing Physical Protection Costs with Restoration Schemes. Physical Layer Topology Considerations. The Problem of Diversity Integrity. Survivability at the Transmission System Layer. “Linear” Transmission Systems. Automatic Protection Switching (APS). Reversion. “Extra Traffic” Feature. AIS Concept. Hitless Switching. Unidirectional Path-Switched Rings (UPSR). Bidirectional Line-Switched Rings (BLSR). Resilient Packet Rings (RPR). Ring Covers. Generalized Loopback Networks. System Layer Protection Without 100% Redundancy: p-Cycles. Logical Layer Survivability Schemes. Concepts of Protection, Restoration and Distributed Preplanning. Span Restoration or Span Protection. Meta-mesh. p-Cycles. Path Restoration. Shared-Backup Path Protection (SBPP). Segmented or Short-Leap Shared Protection (SLSP). GMPLS Automatic Reprovisioning as a Restoration Mechanism. Service Layer Survivability Schemes. Comparative Advantages of Different Layers for Survivability. Measures of Outage and Survivability Performance. McDonald's ULE. The (U,D,E) Framework for Quantifying Service Outages. Measures of Network Survivability. Restorability. Reliability. Availability. Concept of “Unavailability”. Series Unavailability Relationships. Parallel Unavailability Relationships. Series-Parallel Reductions. Network Reliability. Two-Terminal Network Reliability. Factoring the Graph and Conditional Decomposition. Expected Loss of Traffic and of Connectivity. Expected Loss of Traffic (ELT). Annual Expected Downtime of Connection (AEDC).

4. Graph Theory, Routing, and Optimization.

Graph Theory Related to Transport Networking. Set Concepts and Notation. Graph Theory as it Relates to Transport Networks. Transport Network Terminology. Distinct and Disjoint Routes. Data Representations of Graphs. Computational Complexity. Asymptotic Notation. P and NP. Shortest Path Algorithms. Concepts of Labeling and Scanning. The Dijkstra Algorithm. Bhandari's Modified Dijkstra Algorithms. BFS Dijkstra. Modified Dijkstra. k-Shortest Path Algorithms. All Distinct Routes. Maximum Flow: Concept and Algorithm. The Min-Cut Max-Flow Theorem. Maximum Flow Algorithm. The Trap Topology. k-Shortest Paths as an Approximation to Maximum Flow. Shortest Disjoint Path Pair. Finding Biconnected Components of a Graph. The Cut-Tree. Finding All Cycles of a Graph. Fundamental Set of Cycles. Depth-First Search for Cycle Enumeration. Optimization Methods for Network Design. Linear and Integer Programming. The Role and Limitations for Mathematical Programming. General Symbolic Form of an LP or ILP. Example Development of an Optimization Model. Making the Problem an Integer Linear Program. Duality. Unimodularity and Special Structures. Network Flow Problems. The Transportation Problem. Two-Terminal MCNF (or Minimum Cost Routing). Maximum Flow as an MCNF. Multi-Commodity Maximum Flow (MCMF). Maximum Sum Multi-Commodity Maximum Flow (MS-MCMF). Maximum Concurrent MCMF (MConMF). Techniques for Formulating LP/ILP Problems. Mutual Exclusion. Switching. Peak Minimizing. Bicriteria Studies and Pareto Optimal Solutions. Representing Routes and Graph Topology. Modularity of Capacity. Implicit Representation of Functionality. Tips for Getting the Solutions. Lagrangean Techniques. Vector-Matrix Notation for an LP Problem. Lagrange Multipliers. Extension to Inequalities. Lagrangean Relaxation and the Lagrangean Dual. Complexity of LP and ILP. Other Combinatorial Optimization Methods: Meta-Heuristics. Simulated Annealing. Genetic Algorithms. Tabu Search. Comparison of Optimization Techniques.


5. Span-Restorable and Span-Protected Mesh Networks.

Updating the View of Span Restoration. Operational Concepts for Span Restoration. Details of the Span Restoration (SR) Concept. Concept of Distributed Self-Healing Mesh Restoration and DRAs. Self-Organizing Nodal Interaction via Statelets. Distributed Protection Preplanning with a DRA. The Working Capacity Envelope Concept for Dynamic Demands. Demand-Adaptive Definition of the Working Capacity Envelope. Concept of First-Failure Protection and Second-Failure Restoration. Spare Capacity Design of Span-Restorable Mesh Networks. Overview of the Problem. Basic Node-Arc Formulation. Basic Arc-Path Formulation. Herzberg and Bye's Hop-Limited Formulation. Large-Scale Practicality of Hop-Limited Arc-Path SCA. Concept of a Threshold Hop Limit. Cut-Oriented Formulations of the SCA Problem. Venables' Iterated Cutsets Method for SCA. Summary: A Complete Cut-Oriented SCA Methodology. Jointly Optimized Working and Spare Capacity Assignment. Joint Capacity Allocation (JCA) Model. Isolated Nodal Bounding Considerations. Effect of Capacity Balance on Redundancy. Understanding the JCA Benefit. Operational Strategy for JCA-Based Incremental Capacity Planning. The Forcer Concept. Forcer Analysis Procedure. Modular Span-Restorable Mesh Capacity Design. Modular-Aware Spare Capacity Allocation (MSCA). Modular Joint Capacity Allocation (MJCA). Comparative Results with the Modular Design Formulations. Modeling Modularity with Per-Channel Provisioning Costs. A Generic Policy for Generating Eligible Route Sets. Generating Eligible Restoration Route Sets. Generating Eligible Route Sets for Working Paths. Chain Optimized Mesh Design for Low Connectivity Graphs. The Meta-Mesh Concept. Chain Subnetworks Under Ordinary SCA or JCA. Logical Chain Bypass Spans. Restoration in the Bypassed Chains. Design Method to Effect the Meta-Mesh Concept. Sample Results. Span-Restorable Capacity Design with Multiple Service Classes. How Multi-QoP Span Restoration Works. Multi-QoP Capacity Design. Multi-QoP MJCA. Sample Results on Multi-QoP Designs. Approximation Models for Multi-QoP Design. Maximum Revenue Multi-QoP Design. Incremental Capacity Planning for Span-Restorable Networks. What Value for Rearrangeability? Bicriteria Design Methods for Span-Restorable Mesh Networks. Bicriteria Design for Reducing Restoration Path Lengths. Bicriterion Design for Maintenance Risk Reduction. Bicriterion Design for Best Efforts and Preemptible Services.

6. Path Restoration and Shared Backup Path Protection.

Understanding Path Protection, Path Restoration and Path Segments. Is Path Restoration Just Span Restoration Without Loopbacks? Concept of Mutual Capacity in Path Restoration. Experiments Simulating GMPLS Auto Reprovisioning. Network Recovery From Node Loss. A Framework for Path Restoration Routing and Capacity Design. Specifying Failure Scenarios. Specifying Network Structure, Capacity and Eligible Routes. The Path Restoration Rerouting Problem. Concepts of Stub Release and Stub Reuse in Path Restoration. Lower Bounds on Redundancy. Master Formulation for Path Restoration Capacity Design. Simplest Model for Path Restoration Capacity Design. Comparative Study of Span and Path-Restorable Designs. Demand Dispersion and Routing Effects. Shared Backup Path Protection (SBPP). Infeasibility in Greedy Disjoint Path Pairs. Discounting the Shared Backup Path: Asymmetric Path Pairs. Disjoint Primary/Shared Backup Relationships: Venn Diagram. Optimal Design of Shared-Backup Path Protected Networks. Wavelength Assignment Under SBPP. SBPP Design with Limits on the Sharing of Spare Capacity. Capacity Effects of Sharing Limits in SBPP. Arc-Flow Models for SBPP. Lagrangean Relaxation for Path-Oriented Capacity Design Problems. Solution Method for the LR Problem for a Given m Vector. Iterative Maximization of the LR Problem on m. Heuristics for Path-Restorable Network Design. Phase 1 Heuristics—Design Construction. Modeling Existing Capacity. Minimum Incremental Cost Routing. Iterated-Dijkstra to Solve MIC_NF. Alternate Phase 1 Algorithm. Putting Modularity Considerations in the Iterative Heuristic. Concepts of Aggregating Prerouting and Pseudo-Cost Functions. Modular Minimum Incremental Cost Network Flow (mod_MIC_NF). Modular Minimal Incremental Cost Multi-Commodity Network Flow. Phase 2 Forcer-Oriented Design Improvement Heuristic. A Tabu Search Heuristic for Design Tightening. Simulated Allocation Type of Algorithm for Design Tightening. Efficiently Updating the Spare Capacity Design. Classifying Spans by Forcer Status. Path-Shift Strategies for Direct Forcer-Based Improvements.

7. Oversubscription-Based Design of Shared Backup Path Protection for MPLS or ATM.

Concept of Oversubscription. Historical Background and Some Misconceptions. Overview of MPLS Shared Backup Path Protection and ATM Backup VP Concepts. The Oversubscription Design Framework. Defining the Oversubscription Factor Xj,i. KST Algorithm for Backup Path Capacity Allocation. Oversubscription Effects with KST-Alg. Minimum Spare Capacity with Limits on Oversubscription. Minimum Peak Oversubscription with Given Spare Capacity. OS-3: Minimum Total Capacity with Limited Oversubscription. Related Bounds on Spare Capacity. Upper Bound Based on KST Algorithm. Lower Bound Based on the LP Relaxation of OS-1. Illustrative Results and Discussion. The Design Trade-off between Spare Capacity and Xtol. Statistics of Individual Xj,i Values under OS-1 Design. OS-2 Minimization of Oversubscription with Given Capacity. OS-3 Benefit of Jointly Optimizing Primary and Backup Paths. Determining the Maximum Tolerable Oversubscription. Simulation Design for Equivalent Bandwidth. Illustrative Results. Other Comments on Determining Xtol. Extension and Application to Multiple Classes of Service. Adaptive Link-Based Implementation of Priority Schemes.

8. Dual Failures, Nodal Bypass and Common Duct Effects on Design and Availability.

Are Dual Failures a Real Concern? Dual Failure Restorability Analysis of Span-Restorable Networks. Canonical Dual Failure Scenarios. Determining the Network Average Dual Failure Restorability, R2. Computational Approach. Models for the Restoration Process. Experimental Results. Relationship Between Dual Failure Restorability and Availability. Axioms and Role of Availability Analysis of Networks. Average Case Availability of Service Paths. Availability Calculation for a Specific Path. Implications for an Ultra-High Availability Class of Service. Link to the 1FP-2FR Concept. Dual Failure Availability Analysis for SBPP Networks. Experimental Comparison of SBPP and Span Restoration. Optimizing Spare Capacity Design for Dual Failures. Minimum Capacity to Withstand All Dual Failures (DFMC). Dual Failure Maximum Restorability (DFMR). Pure Redistribution of Spare Capacity to Enhance R2. Multi-Service Restorability Capacity Placement Design (MRCP). Experimental Results. Dual Failure Considerations Arising From Express Routes. Express Routes and Nodal Bypass. Does a Nodal Bypass Require Increased Spare Capacity? When Does Bypass Yield a Spare Capacity Reduction? Optimal Capacity Design with Bypasses. Minimum Spare Capacity Given a Set of Express Routes. Allowing the Model to Dimension the Express Routes. Maximum Port Elimination by Bypass at Minimum Spare Capacity. Sample Results. Iterative Optimization of Express Routes. Effects of Dual Failures Arising from Shared Risk Link Groups. Comparing Span SRLG and Bypass Dual-Failure Situations. Capacity Design for a Known Set of SRLGs. Effects of SRLGs on Spare Capacity. Randomly Occurring SRLGs. Availability Benefit of Coincident SRLG Design Coverage. Predicting the Impact of a Specific SRLG. Effects of Nodal Degree. Effects of Topological Location. Effects of Working Capacity Disparity. Benefit of Removing the Most Troublesome SRLGs. SRLG Effects on Other Protection Schemes.

9. Mesh Network Topology Design and Evolution.

Different Contexts and Benefits of Topology Planning. Topology Design for Working Flow Only. Branch Exchange. Cut Saturation. The MENTOR Algorithm. Yaged's Fixed Point Convergence Method. The Fixed Charge and Routing (FCR) Problem. Interacting Effects in Mesh-Survivable Topology. Experimental Studies of Mesh Capacity versus Graph Connectivity. How Economy of Scale Changes the Optimal Topology. The Single-Span Addition Problem. How “Partial Express” Flows Can Suggest New Spans. Frequency and Remoteness Metrics for Prospective Span Additions. Overall Study Technique for Single-Span Additions. The Complete Mesh Topology, Routing, and Spare Capacity Problem. Added Valid Knowledge Constraints. Relaxations. Complexity of MTRS. Sample Results: Studies with MTRS. Effect of Edge-to-Capacity Cost Ratio, W. Effect of Demand Intensity and Demand Pattern. A Three-Part Heuristic for MTRS. Step W1: Working-only Fixed Charge Plus Routing. Step S2: Reserve Network Fixed Charge and Sparing (RN-FCS). Step J3: Restricted MTRS for Final Topology Selection. Useful Bounds from Steps W1 and J3. Studies with the Three-Part Heuristic for MTRS. Method. Results. Discussion. Insights from the Three-Part Heuristic. Ezema's Edge-Limiting Criteria. Successive Inclusion Heuristic. Graph Sifting and Graph Repair for Topology Search. Graph Generation. Graph Testing. Repair Procedures. A Tabu Search Extension of the Graph Sifter Architecture. Range Sweeping Topology Search. Sample Results with Sweep Search. Overall Strategy and Applications for Topology Planning.

10. p-Cycles.

The Concept of p-Cycles. Why Straddling Spans Are So Significant. Historical Origins: Preconfiguration and the “Clamshell” Diagram. Other Important Properties of p-Cycles. Enhanced Rings. Cycle Covers and “Protection Cycles” per Ellinas et al. Optimal Capacity Design of Networks with p-Cycles. Concept of “Useful Paths” for p-Cycle Design. Maximum p-Cycle Restorability with a Given Spare Capacity. Minimum Spare Capacity for 100% p-Cycle Restorability. Adding a Span Capacity Constraint. Results with Basic Capacity Formulations. Joint Optimization of Working Path Routing and p-Cycle Placement. Application of p-Cycles to DWDM Networks. Wavelength Continuity—the WP case. Dark-Fiber p-Cycles: Protection without any Wavelength Conversion. p-Cycle Wavelength Path (WP) Design Problems. Summary and Discussion of p-Cycle Design Models. Schupke et al — Case Study for DWDM p-Cycles. VWP Results. Computation Times. Placing Wavelength Converters at the p-Cycle Access Points Only. Results with Jointly Optimized (VWP) p-Cycles. Heuristic and Algorithmic Approaches to p-Cycle Design. p-Cycle Efficiency Metrics. The “Perfect Score” for a p-Cycle. A Score-Based Design Assembly Algorithm. Preselection of Candidate p-Cycles: a Heuristic for MIP Solutions. Results with Preselection to Solve the Joint p-Cycle Design Problem. Zhang and Yang's Straddling Span Algorithm. Add and Join Operations on Primary p-Cycles. Application of Add/Join Operations to Design Improvement. General p-Cycle Merge Operation. Simulated Allocation Approach for Joint Design Algorithms. Concept of a Straddling Subnetwork and Domain Perimeter p-Cycles. Extra Straddling Relationships with Non-Simple p-Cycles. Hamiltonian p-Cycles and Homogeneous Networks. Concept of a Homogeneous Network. The Role of Hamiltonian p-Cycles in Ordinary Capacitated Designs. p-Cycle Design in Homogeneous Hamiltonian Networks. Lower Bounds for p-Cycles on a Hamiltonian Network. Semi-Homogeneous Networks Inspired by p-Cycles. An ADM-like Nodal Device for p-Cycles. Self-Organized p-Cycle Formation. Virtual p-Cycles in the MPLS Layer for Link and Node Protection. IP Link Restoration with MPLS p-Cycles. Network Design using MPLS p-Cycles for Link Restoration. Node-Encircling p-Cycles for Protection Against Node Loss. Types of Node-Encircling p-Cycles. Rerouting Mechanism with Node-Encircling p-Cycles. Generating Node Encircling p-Cycles. On the Prospect of Using Only Node-Encircling p-Cycles.

11. Ring-Mesh Hybrids and Ring-to-Mesh Evolution.

Integrated ADM Functions on DCS/OXC: an Enabler of Hybrids. Hybrids Based on the Ring-Access Mesh-Core Principle. Core and Access Network Partitioning. Access Ring Formation and Span Elimination. Mesh-Chain Hybrid Networks. Studies of Ring-Mesh and Mesh-Chain Hybrid Network Designs. Design of the Ring-Mesh Hybrids. Pure Mesh and Mesh-Chain Designs. Pure Ring Reference Designs. Results and Discussion. Optimal Design of Ring-Mesh Hybrids. Concept of a Single-Layer Ring-Mesh Hybrid Transport Network. Cost Modeling for Ring-Mesh Hybrids. Ring-Mesh Hybrid Design Model. Forcer Clipping Ring-Mesh Hybrids. The Forcer Clipping Hypothesis. Forcer Clipping Heuristics. Methodology for Tests of the Forcer Clipping Heuristics. Results and Discussion. Ring to Mesh Evolution via “Ring Mining”. Optimization Model for Pure Ring Mining. Ring Network Designs for Tests of Ring Mining. Test Results for Pure Ring Mining. Ring Mining with Minimum Cost Capacity Additions. Minimum Cost Evolutionary Strategy with Conversion Costs. Implementation of Ring Mining Strategies. Ring Mining to p-Cycles as the Target Architecture. Converting Rings into Modular p-Cycles: Nodal View. Network Level View of Evolution from Rings to p-Cycles.



Download the Index file related to this title.


Submit Errata

More Information

InformIT Promotional Mailings & Special Offers

I would like to receive exclusive offers and hear about products from InformIT and its family of brands. I can unsubscribe at any time.


Pearson Education, Inc., 221 River Street, Hoboken, New Jersey 07030, (Pearson) presents this site to provide information about products and services that can be purchased through this site.

This privacy notice provides an overview of our commitment to privacy and describes how we collect, protect, use and share personal information collected through this site. Please note that other Pearson websites and online products and services have their own separate privacy policies.

Collection and Use of Information

To conduct business and deliver products and services, Pearson collects and uses personal information in several ways in connection with this site, including:

Questions and Inquiries

For inquiries and questions, we collect the inquiry or question, together with name, contact details (email address, phone number and mailing address) and any other additional information voluntarily submitted to us through a Contact Us form or an email. We use this information to address the inquiry and respond to the question.

Online Store

For orders and purchases placed through our online store on this site, we collect order details, name, institution name and address (if applicable), email address, phone number, shipping and billing addresses, credit/debit card information, shipping options and any instructions. We use this information to complete transactions, fulfill orders, communicate with individuals placing orders or visiting the online store, and for related purposes.


Pearson may offer opportunities to provide feedback or participate in surveys, including surveys evaluating Pearson products, services or sites. Participation is voluntary. Pearson collects information requested in the survey questions and uses the information to evaluate, support, maintain and improve products, services or sites, develop new products and services, conduct educational research and for other purposes specified in the survey.

Contests and Drawings

Occasionally, we may sponsor a contest or drawing. Participation is optional. Pearson collects name, contact information and other information specified on the entry form for the contest or drawing to conduct the contest or drawing. Pearson may collect additional personal information from the winners of a contest or drawing in order to award the prize and for tax reporting purposes, as required by law.


If you have elected to receive email newsletters or promotional mailings and special offers but want to unsubscribe, simply email information@informit.com.

Service Announcements

On rare occasions it is necessary to send out a strictly service related announcement. For instance, if our service is temporarily suspended for maintenance we might send users an email. Generally, users may not opt-out of these communications, though they can deactivate their account information. However, these communications are not promotional in nature.

Customer Service

We communicate with users on a regular basis to provide requested services and in regard to issues relating to their account we reply via email or phone in accordance with the users' wishes when a user submits their information through our Contact Us form.

Other Collection and Use of Information

Application and System Logs

Pearson automatically collects log data to help ensure the delivery, availability and security of this site. Log data may include technical information about how a user or visitor connected to this site, such as browser type, type of computer/device, operating system, internet service provider and IP address. We use this information for support purposes and to monitor the health of the site, identify problems, improve service, detect unauthorized access and fraudulent activity, prevent and respond to security incidents and appropriately scale computing resources.

Web Analytics

Pearson may use third party web trend analytical services, including Google Analytics, to collect visitor information, such as IP addresses, browser types, referring pages, pages visited and time spent on a particular site. While these analytical services collect and report information on an anonymous basis, they may use cookies to gather web trend information. The information gathered may enable Pearson (but not the third party web trend services) to link information with application and system log data. Pearson uses this information for system administration and to identify problems, improve service, detect unauthorized access and fraudulent activity, prevent and respond to security incidents, appropriately scale computing resources and otherwise support and deliver this site and its services.

Cookies and Related Technologies

This site uses cookies and similar technologies to personalize content, measure traffic patterns, control security, track use and access of information on this site, and provide interest-based messages and advertising. Users can manage and block the use of cookies through their browser. Disabling or blocking certain cookies may limit the functionality of this site.

Do Not Track

This site currently does not respond to Do Not Track signals.


Pearson uses appropriate physical, administrative and technical security measures to protect personal information from unauthorized access, use and disclosure.


This site is not directed to children under the age of 13.


Pearson may send or direct marketing communications to users, provided that

  • Pearson will not use personal information collected or processed as a K-12 school service provider for the purpose of directed or targeted advertising.
  • Such marketing is consistent with applicable law and Pearson's legal obligations.
  • Pearson will not knowingly direct or send marketing communications to an individual who has expressed a preference not to receive marketing.
  • Where required by applicable law, express or implied consent to marketing exists and has not been withdrawn.

Pearson may provide personal information to a third party service provider on a restricted basis to provide marketing solely on behalf of Pearson or an affiliate or customer for whom Pearson is a service provider. Marketing preferences may be changed at any time.

Correcting/Updating Personal Information

If a user's personally identifiable information changes (such as your postal address or email address), we provide a way to correct or update that user's personal data provided to us. This can be done on the Account page. If a user no longer desires our service and desires to delete his or her account, please contact us at customer-service@informit.com and we will process the deletion of a user's account.


Users can always make an informed choice as to whether they should proceed with certain services offered by InformIT. If you choose to remove yourself from our mailing list(s) simply visit the following page and uncheck any communication you no longer want to receive: www.informit.com/u.aspx.

Sale of Personal Information

Pearson does not rent or sell personal information in exchange for any payment of money.

While Pearson does not sell personal information, as defined in Nevada law, Nevada residents may email a request for no sale of their personal information to NevadaDesignatedRequest@pearson.com.

Supplemental Privacy Statement for California Residents

California residents should read our Supplemental privacy statement for California residents in conjunction with this Privacy Notice. The Supplemental privacy statement for California residents explains Pearson's commitment to comply with California law and applies to personal information of California residents collected in connection with this site and the Services.

Sharing and Disclosure

Pearson may disclose personal information, as follows:

  • As required by law.
  • With the consent of the individual (or their parent, if the individual is a minor)
  • In response to a subpoena, court order or legal process, to the extent permitted or required by law
  • To protect the security and safety of individuals, data, assets and systems, consistent with applicable law
  • In connection the sale, joint venture or other transfer of some or all of its company or assets, subject to the provisions of this Privacy Notice
  • To investigate or address actual or suspected fraud or other illegal activities
  • To exercise its legal rights, including enforcement of the Terms of Use for this site or another contract
  • To affiliated Pearson companies and other companies and organizations who perform work for Pearson and are obligated to protect the privacy of personal information consistent with this Privacy Notice
  • To a school, organization, company or government agency, where Pearson collects or processes the personal information in a school setting or on behalf of such organization, company or government agency.


This web site contains links to other sites. Please be aware that we are not responsible for the privacy practices of such other sites. We encourage our users to be aware when they leave our site and to read the privacy statements of each and every web site that collects Personal Information. This privacy statement applies solely to information collected by this web site.

Requests and Contact

Please contact us about this Privacy Notice or if you have any requests or questions relating to the privacy of your personal information.

Changes to this Privacy Notice

We may revise this Privacy Notice through an updated posting. We will identify the effective date of the revision in the posting. Often, updates are made to provide greater clarity or to comply with changes in regulatory requirements. If the updates involve material changes to the collection, protection, use or disclosure of Personal Information, Pearson will provide notice of the change through a conspicuous notice on this site or other appropriate way. Continued use of the site after the effective date of a posted revision evidences acceptance. Please contact us if you have questions or concerns about the Privacy Notice or any objection to any revisions.

Last Update: November 17, 2020