Although the Internet Archive's Wayback Machine is the largest and most well-known web archive, there have been a number of public web archives that have emerged in the last several years. With varying resources, audiences and collection development policies, these archives have varying levels of overlap with each other. While individual archives can be measured in terms of number of URIs, number of copies per URI, and intersection with other archives, to date there has been no answer to the question "How much of the Web is archived?" We study the question by approximating the Web using sample URIs from DMOZ, Delicious, Bitly, and search engine indexes; and, counting the number of copies of the sample URIs exist in various public web archives. Each sample set provides its own bias. The results from our sample sets indicate that range from 35%-90% of the Web has at least one archived copy, 17%-49% has between 2-5 copies, 1%-8% has 6-10 copies, and 8%-63% has more than 10 copies in public web archives. The number of URI copies varies as a function of time, but no more than 31.3% of URIs are archived more than once per month.

When a user views an archived page using the archive's user interface (UI), the user selects a datetime to view from a list. The archived web page, if available, is then displayed. From this display, the web archive UI attempts to simulate the web browsing experience by smoothly transitioning between archived pages. During this process, the target datetime changes with each link followed; drifting away from the datetime originally selected. When browsing sparselyarchived pages, this nearly-silent drift can be many years in just a few clicks. We conducted 200,000 acyclic walks of archived pages, following up to 50 links per walk, comparing the results of two target datetime policies. The Sliding Target policy allows the target datetime to change as it does in archive UIs such as the Internet Archive's Wayback Machine. The Sticky Target policy, represented by the Memento API, keeps the target datetime the same throughout the walk. We found that the Sliding Target policy drift increases with the number of walk steps, number of domains visited, and choice (number of links available). However, the Sticky Target policy controls temporal drift, holding it to less than 30 days on average regardless of walk length or number of domains visited. The Sticky Target policy shows some increase as choice increases, but this may be caused by other factors. We conclude that based on walk length, the Sticky Target policy generally produces at least 30 days less drift than the Sliding Target policy.

When a user retrieves a page from a web archive, the page is marked with the acquisition datetime of the root resource, which effectively asserts "this is how the page looked at a that datetime." However, embedded resources, such as images, are often archived at different datetimes than the main page. The presentation appears temporally coherent, but is composed from resources acquired over a wide range of datetimes. We examine the completeness and temporal coherence of composite archived resources (composite mementos) under two selection heuristics. The completeness and temporal coherence achieved using a single archive was compared to the results achieved using multiple archives. We found that at most 38.7% of composite mementos are both temporally coherent and that at most only 17.9% (roughly 1 in 5) are temporally coherent and 100% complete. Using multiple archives increases mean completeness by 3.1-4.1% but also reduces temporal coherence.

Most archived HTML pages embed other web resources, such as images and stylesheets. Playback of the archived web pages typically provides only the capture date (or Memento-Datetime) of the root resource and not the Memento-Datetime of the embedded resources. In the course of our research, we have discovered that the Memento-Datetime of embedded resources can be up to several years in the future or past, relative to the Memento-Datetime of the embedding root resource. We introduce a framework for assessing temporal coherence between a root resource and its embedded resource depending on Memento-Datetime, Last-Modified datetime, and entity body.

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One of the major challenges in wireless sensor networks(WSNs) design lies in the constrained energy available to sensor nodes. Workforce selection strategies which unevenly consume sensor energy can reduce the lifetime of the network significantly. This work proposes and evaluates a new class of strategies that provides an energy efficient workforce management for WSNs. Analytical and simulation results demonstrate that the proposed approach significantly increases network lifetime by evenly consuming sensors power.

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